Human psychology contains adaptations to deploy aggression as one solution to many distinct adaptive problems. These include expropriating resources, defending against incursions, establishing encroachment-deterring reputations, inflicting costs on rivals, ascending dominance hierarchies, dissuading partner defection, eliminating fitness-draining offspring, and obtaining new mates. Aggression is not a singular strategy. Comprehensive theories must identify the of multiple adaptations for aggression.

Boehm's paper is a piece of speculation, but of careful and empirically founded speculation, which is stimulating methodologically and empirically. Being a cultural anthropologist, I will confine my comments mainly to the parts of Boehm's argument concerned with social control mechanisms using moral pressure.

Creativity is commonly seen as beyond the scope of rationality. In the present paper, it is argued that available insights in epistemology and available results in logic enable us to incorporate creativity within an independently sensible view on human rationality.

Integrative systems biology is an emerging field that attempts to integrate computation, applied mathematics, engineering concepts and methods, and biological experimentation in order to model large-scale complex biochemical networks. The field is thus an important contemporary instance of an interdisciplinary approach to solving complex problems. Interdisciplinary science is a recent topic in the philosophy of science. Determining what is philosophically important and distinct about interdisciplinary practices requires detailed accounts of problem-solving practices that attempt to understand how specific (...) practices address the challenges and constraints of interdisciplinary research in different contexts. In this paper we draw from our 5-year empirical ethnographic study of two systems biology labs and their collaborations with experimental biologists to analyze a significant problem-solving approach in ISB, which we call adaptive problem solving. ISB lacks much of the methodological and theoretical resources usually found in disciplines in the natural sciences, such as methodological frameworks that prescribe reliable model-building processes. Researchers in our labs compensate for the lack of these and for the complexity of their problems by using a range of heuristics and experimenting with multiple methods and concepts from the background fields available to them. Using these resources researchers search out good techniques and practices for transforming intractable problems into potentially solvable ones. The relative freedom lab directors grant their researchers to explore methodological options and find good practices that suit their problems is not only a response to the complex interdisciplinary nature of the specific problem, but also provides the field itself with an opportunity to discover more general methodological approaches and develop theories of biological systems. Such developments in turn can help to establish the field as an identifiably distinct and successful approach to understanding biological systems. (shrink)

The issue on the role of users in knowledge-based systems can be investigated from two aspects: the design aspect and the functionality aspect. Participatory design is an important approach for the first aspect while system adaptability supported by user modelling is crucial to the second aspect. In the article, we discuss the second aspect. We view a knowledge-based computer system as the partner of users' problem-solving process, and we argue that the system functionality can be enhanced by adapting (...) the behaviour of the system to fit the needs of users with different profiles. We emphasise that the notion of user modelling is crucial to realise such kind of flexibility. User modelling will be beneficial to the user, not only through adaptive interfaces, but also through the enhanced system adaptability. In a knowledge-based system, by incorporating user models, searching can be reduced to a smaller portion in the knowledge-base, thus enhancing system functionality. In other words, user modelling is incorporated to realise flexible inference control to achieve system adaptability. An example is provided, and a general conceptual model is sketched. We conclude this paper by emphasising that the design aspect and functionality aspect are complementary. Achieving enhanced functionality through joint efforts of computers and human users indicates a kind of participatory execution of computerised problem-solving or participatory problem-solving. (shrink)

The current research investigates a combination of two instructional approaches, tutored problem solving and worked examples. Tutored problem solving with automated tutors has proven to be an effective instructional method. Worked‐out examples have been shown to be an effective complement to untutored problem solving, but it is largely unknown whether they are an effective complement to tutored problem solving. Further, while computer‐based learning environments offer the possibility of adaptively transitioning from examples to (...) problems while tailoring to an individual learner, the effectiveness of such machine‐adapted example fading is largely unstudied. To address these research questions, one lab and one classroom experiment were conducted. Both studies compared a standard Cognitive Tutor with two example‐enhanced Cognitive Tutors, in which the fading of worked‐out examples occurred either in a fixed way or adaptively. Results indicate that the adaptive fading of worked‐out examples leads to higher transfer performance on delayed posttests than the other two methods. (shrink)

The paper identifies defining characteristics of the principal models of problem-solving behavior which are useful in developing a general theory of problem-solving. An attempt is made both to make explicit those disagreements between theorists of different persuasions which have served as obstacles to an integrated approach, and to show that these disagreements have arisen from a number of conceptual confusions: The conflict between information processors and behavioral analysts has resulted from a common failure to understand theoretical (...) sufficiency, and hence these theorists have been at a loss to understand one another. Two directions of research in problem-solving, mechanical algorithmic problem-solving and the psychology of invention, have been thought to be divergent, but in fact complement one another once it is clear that problem-solving involves neither discovery nor invention, but rather is a matter of perceptual encoding and processing. Successful problem-solving behavior can be described as adaptive, learning behavior in which organization skills are effectively associated with situationally determined perceptual encoding processes of the individual mechanical or biological problem-solver. (shrink)

In this paper, we bring together research on complex problem solving with that on motivational psychology about goal setting. Complex problems require motivational effort because of their inherent difficulties. Goal Setting Theory has shown with simple tasks that high, specific performance goals lead to better performance outcome than do-your-best goals. However, in complex tasks, learning goals have proven more effective than performance goals. Based on the Zurich Resource Model, so-called motto-goals should activate a person’s resources through positive affect. (...) It was found that motto-goals are effective with unpleasant duties. Therefore, we tested the hypothesis that motto-goals outperform learning and performance goals in the case of complex problems. A total of N = 123 subject participated in the experiment. In dependence of their goal condition, subjects developed a personal motto, learning, or performance goal. This goal was adapted for the computer-simulated complex scenario Tailorshop, where subjects worked as managers in a small fictional company. Other than expected, there was no main effect of goal condition for the management performance. An unexpected gender effect revealed better performance for men than women, pointing to a potential stereotype threat. As hypothesized, motto goals led to higher positive and lower negative affect than the other two goal types. Even though positive affect decreased and negative affect increased in all three groups during Tailorshop completion, participants with motto goals reported the lowest rates of negative affect. Exploratory analyses investigated the role of affect in complex problem solving via mediational analyses and the influence of goal type on perceived goal attainment. (shrink)

The study of insight problem solving could well become one of the most important topics in the contemporary debate on thought. Dealing with insight problems today requires of necessity reconsidering the concept of bounded rationality. Simon’s work has inspired us to reflect on the specific quality of the type of boundaries which, by limiting the search, allow and guarantee the act of creativity; finding the solution to insight problems is emblematic of this creativity and provides a paradigmatic case. (...) According to Simon, the solution to insight problems requires a search for an alternative space. He considered the “Notice Invariants Heuristic” to be a powerful tool for focusing this search which must always be guided by salience. Therefore, in the case of insight problems the heuristic is not a weak method of solving problems; indeed, it is the only way, an innovative and creative approach to reach the solution. In our view, the solution to these problems is not attained by abstraction, but only by a pertinent interpretation of the context (interpretative heuristic) in the light of the goal, allowing the problem solver to abandon the default representation. We therefore propose that this interpretative heuristic is inherent to all insight problem solving processes and, in more general terms, is an adaptive characteristic of the human cognitive system; this of course implies that the dual process theory will have to be challenged and discussed. (shrink)

We hypothesize that effective collaboration is facilitated when individuals and environmental components form a synergy where they work together and regulate one another to produce stable patterns of behavior, or regularity, as well as adaptively reorganize to form new behaviors, or irregularity. We tested this hypothesis in a study with 32 triads who collaboratively solved a challenging visual computer programming task for 20 min following an introductory warm‐up phase. Multidimensional recurrence quantification analysis was used to examine fine‐grained (i.e., every 10 (...) s) collective patterns of regularity across team members' speech rate, body movement, and team interaction with the shared user interface. We found that teams exhibited significant patterns of regularity as compared to shuffled baselines, but there were no systematic trends in regularity across time. We also found that periods of regularity were associated with a reduction in overall behavior. Notably, the production of irregular behavior predicted expert‐coded metrics of collaborative activity, such as teams' ability to construct shared knowledge and effectively negotiate and coordinate execution of solutions, net of overall behavioral production and behavioral self‐similarity. Our findings support the theory that groups can interact to form interpersonal synergies and indicate that information about system‐level dynamics is a viable way to understand and predict effective collaborative processes. (shrink)

Much of our thinking focuses on deciding what to do in situations where the space of possible options is too large to evaluate exhaustively. Previous work has found that people do this by learning the general value of different behaviors, and prioritizing thinking about high-value options in new situations. Is this good-action bias always the best strategy, or can thinking about low-value options sometimes become more beneficial? Can people adapt their thinking accordingly based on the situation? And how do we (...) know what to think about in novel events? Here, we developed a block-puzzle paradigm that enabled us to measure people's thinking plans and compare them to a computational model of rational thought. We used two distinct response methods to explore what people think about—a self-report method, in which we asked people explicitly to report what they thought about, and an implicit response time method, in which we used people's decision-making times to reveal what they thought about. Our results suggest that people can quickly estimate the apparent value of different options and use this to decide what to think about. Critically, we find that people can flexibly prioritize whether to think about high-value options (Experiments 1 and 2) or low-value options (Experiments 3, 4, and 5), depending on the problem. Through computational modeling, we show that these thinking strategies are broadly rational, enabling people to maximize the value of long-term decisions. Our results suggest that thinking plans are flexible: What we think about depends on the structure of the problems we are trying to solve. (shrink)

Operational failures in hospitals, such as communication breakdowns and equipment malfunctions, challenge nurses by disrupting patient care, workflow, and clinical processes. These failures are primarily addressed with short‐term solutions, rather than comprehensive, long‐term strategies. This study investigates the impact of operational failures on patients and examines whether nurses alter their problem‐solving behavior in response to the perceived direct impact on patients. A qualitative, exploratory study was conducted in 23 wards across five Belgian hospitals. Data were collected through in‐depth (...) semi‐structured interviews with 26 nurses and a group discussion with ward managers (n = 6). Findings reveal that barriers such as nurses' limited awareness regarding the broader impact of operational failures on patients, poor communication, and excessive workloads hinder problem‐solving efforts. However, when operational failures result in patient harm, nurses are more likely to take corrective action to prevent recurrence. Enablers to enhance problem‐solving behaviors include using narrative medicine to highlight patient safety risks, improvements to communication frameworks, the streamlining of reporting systems, and the allocation of adequate time and resources to address underlying issues. Furthermore, a proactive approach, grounded in Safety‐II principles, emphasizes nurses' flexibility and adaptability, recognizing their indispensable role in learning from successful outcomes and making real‐time adjustments to strengthen resilience within healthcare systems. (shrink)

An interdisciplinary approach to legal education is a process of educating law that encompasses courses from other disciplines. An interdisciplinary course is essential for law students to improve complete outlook on legal issues. The interdisciplinary approach creates effective legal findings. The study objective is to explore the role of interdisciplinary approaches to revolutionizing legal education for the 21st century, focused on the benefits of legal education to enhance students’ problem-solving skills and innovative thinking. Both quantitative and qualitative research (...) methods were used in this study. A total number of 800 structured questionnaires were distributed to individuals. The data collection lasted nearly 27 days. 785 valid responses were received from the participants. The data were analyzed using SPSS software. The valid responses are used to recognize the role of interdisciplinary approaches in legal education. The research found that interdisciplinary approaches in legal education develop students’ problem-solving skills and innovative thinking. The interdisciplinary approach helps to improve students’ ability to solve complex problems comprehensively. Legal education increases graduates’ ability to adapt to the changing demands of the 21st-century legal profession. This study enhances law students’ problem-solving skills through interdisciplinary approaches in legal education. The study highlights innovative thinking, understanding of complex legal issues, graduates’ adaptability, and greater competence. This study’s novelty lies in scrutinizing the advantages of interdisciplinary approaches to revolutionizing legal education for the 21st century. (shrink)

Second, this collection of cognitive programs evolved in the Pleistocene to solve the adaptive problems regularly faced by our hunter-gatherer ancestors-...

ContextBehavioral observation scales are important for understanding and assessing social skills. In the context of collaborative problem-solving (CPS) skills, considered essential in the 21st century, there are no validated scales in French that can be adapted to different CPS tasks. The aim of this study is to adapt and validate, by annotating a new video corpus of dyadic interactions that we have collected, two observational scales allowing us to qualitatively assess CPS skills: the Social Performance Rating Scale (SPRS) (...) and the Social Skills of Collaboration Scale (SSC).MethodThe construct validity of these two scales was assessed by exploratory factor analysis and inter-item correlations. We also checked inter-judge agreement using inter-class correlation coefficients. Internal consistency was determined using Cronbach’s alpha and convergent and divergent validity by assessing correlations between the two scales and measures of depression and alexithymia. Finally, the discriminative properties of the two scales were analyzed by comparing the scores obtained by a group of anxious individuals and a non-anxious control group.ResultsThe results show that our two scales have excellent inter-item correlations. Internal consistency is excellent (alpha SPRS =0.90; SSC = 0.93). Inter-rater agreement ranged from moderate to high. Finally, convergent validity was significant with the alexithymia scale, as was divergent validity with the depression scale. Anxious individuals had lower scores on both scales than non-anxious individuals.ConclusionBoth scales show good psychometric properties for assessing social skills relevant to different collaborative tasks. They also identify individuals with difficulties in social interaction. Thus, they could allow monitoring the effectiveness of training social skills useful in CPS. (shrink)

The present volume intends an incursion into some key techniques of social work practice. Using arguments of social epistemology, the author introduces an overview of the case work and brings to attention important aspects of social work counselling. The reader is challenged to explore methodological aspects of counselling and is encouraged to practice the use of NLP techniques during the nondirective interview, which is able to lead to a change focused on the strengths of the client. Putting into relation the (...) main occupations used in assistance-work creates the complex context of inter and multidisciplinary approach of social work practice, recognizing the border aspect of the discipline. The whole approach proposed by the author is filtered by the ethical character of social intervention directed towards the promotion of individual rights and having as central concept the quality of life. This is not viewed as an abstract concept, but as a source of operational indicators relevant to individual existence. To validate social work as applied science, the author brings into focus epistemological arguments adapted to the requirements and demands of this field. (shrink)

Making adaptive choices between solution strategies is a central element of contemporary mathematics education. However, previous studies signal that students make suboptimal choices between mental and written strategies to solve division problems. In particular, some students of a lower math ability level appear inclined to use mental strategies that lead to lower performance. The current study uses a pretest-training-posttest design to investigate the extent to which these students’ choices for written strategies and performance may be increased. Sixth graders of (...) below-average mathematics level (N = 147) participated in one of two training conditions: an explicit-scaffolding training designed to promote writing down calculations or a practice-only training where strategy use was not explicitly targeted. Written strategy choices and performance increased considerably from pretest to posttest for students in both training conditions, but not in different amounts. Exploratory results suggest that students’ strategy choices may also be affected by their attitudes and beliefs and the sociocultural context regarding strategy use. (shrink)

Can the output of human cognition be predicted from the assumption that it is an optimal response to the information-processing demands of the environment? A methodology called rational analysis is described for deriving predictions about cognitive phenomena using optimization assumptions. The predictions flow from the statistical structure of the environment and not the assumed structure of the mind. Bayesian inference is used, assuming that people start with a weak prior model of the world which they integrate with experience to develop (...) stronger models of specific aspects of the world. Cognitive performance maximizes the difference between the expected gain and cost of mental effort. Memory performance can be predicted on the assumption that retrieval seeks a maximal trade-off between the probability of finding the relevant memories and the effort required to do so; in categorization performance there is a similar trade-off between accuracy in predicting object features and the cost of hypothesis formation; in casual inference the trade-off is between accuracy in predicting future events and the cost of hypothesis formation; and in problem solving it is between the probability of achieving goals and the cost of both external and mental problem-solving search. The implemention of these rational prescriptions in neurally plausible architecture is also discussed. (shrink)

Deontic reasoning is reasoning about permission and obligation: what one may do and what one must do, respectively. Conceivably, people could reason about deontic matters using a purely formal deontic calculus. I review evidence from a range of psychological experiments suggesting that this is not the case. Instead, I argue that deontic reasoning is supported by a collection of dissociable cognitive adaptations for solving adaptive problems that likely would have confronted ancestral humans.

Robustness of a supply network highly depends on its structure. Although structural design methods have been proposed to create supply networks with optimal robustness, a real-life supply network can be quite different from these optimal structural designs. Meanwhile, real cases such as Thailand floods and Tohoku earthquake demonstrate the vulnerability of supply networks in real life. Obviously, it is urgent to enhance the robustness of existing real-life supply networks. Thus, in this paper, a supply network reconfiguration method based on (...) class='Hi'>adaptive variable neighborhood search is proposed to enhance the structural robustness of supply networks facing both random and target disruptions. Firstly, a supply network model considering the heterogeneous roles of entities is introduced. Based on the model, two robustness metrics, Rr and Rt, are proposed to describe the tolerance of supply networks facing random and target disruptions, respectively. Then, the problem of reconfiguration-based supply network robustness enhancement is described. To solve the problem effectively and efficiently, a new heuristic based on general variable neighborhood search, namely, AVNS, is proposed. Finally, a case study based on three real-life supply networks is presented to verify the applicability and effectiveness of the proposed robustness enhancing method. (shrink)

This research investigates the development of transferable - "adaptive" expertise. The study contrasts problem-solving performance of two kinds of experts (business consultants and restaurant managers) on novel problems at the intersection of their two domains, as well as a group of novices (non-business undergraduates). Despite a lack of restaurant experience, consultants performed better than restaurant managers and undergraduates, even though the problems concerned a restaurant. Process measures suggest this was due to the use of more theoretical reasoning. (...) Analyses show this resulted from differences in work experience and not other factors (e.g., education). We discuss aspects of experience that might be responsible for development of theoretical understanding and, thus, expertise that transfers to novel problems. One possible explanation, consistent with existing research from multiple approaches, is that to transfer to novel problems, experience must include substantive variability. The social context of learning may also play a role. (shrink)

Five studies examined how interacting with the physical environment can support the development of fraction concepts. Nine‐ and 10‐year‐old children worked on fraction problems they could not complete mentally. Experiments 1 and 2 showed that manipulating physical pieces facilitated children's ability to develop an interpretation of fractions. Experiment 3 demonstrated that when children understood a content area well, they used their interpretations to repurpose many environments to support problem solving, whereas when they needed to learn, they were prone (...) to the structure of the environment. Experiments 4 and 5 examined transfer after children had learned by manipulating physical pieces. Children who learned by adapting relatively unstructured environments transferred to new materials better than children who learned with “well‐structured” environments that did not require equivalent adaptation. Together, the findings reveal that during physically distributed learning, the opportunity to adapt an environment permits the development of new interpretations that can advance learning. (shrink)

An adaptive neural network control problem is addressed for a class of nonlinear hydraulic servo-systems with time-varying state constraints. In view of the low precision problem of the traditional hydraulic servo-system which is caused by the tracking errors surpassing appropriate bound, the previous works have shown that the constraint for the system is a good way to solve the low precision problem. Meanwhile, compared with constant constraints, the time-varying state constraints are more general in the actual (...) systems. Therefore, when the states of the system are forced to obey bounded time-varying constraint conditions, the high precision tracking performance of the system can be easily realized. In order to achieve this goal, the time-varying barrier Lyapunov function is used to prevent the states from violating time-varying constraints. By the backstepping design, the adaptive controller will be obtained. A radial basis function neural network is used to estimate the uncertainties. Based on analyzing the stability of the hydraulic servo-system, we show that the error signals are bounded in the compacts sets; the time-varying state constrains are never violated and all singles of the hydraulic servo-system are bounded. The simulation and experimental results show that the tracking accuracy of system is improved and the controller has fast tracking ability and strong robustness. (shrink)

This paper tries to explain how individuals manage adaptive individual choice (i.e., the decision to acquire a fitter than average behavior or idea rapidly and tractably) in cultural evolution, despite the fact that acquiring fitness information is very difficult. I argue that the means of solving this problem suggested in the cultural evolution literature largely are various types of decision rules employing representations of fitness correlated properties or states of affairs. I argue that the problem of (...) adaptive individual choice is best solved where some of these learning rule representations are socially transmitted and some are biologically transmitted. (shrink)

This study deals with the problem of radar waveform design based on the weighted mutual information and the difference of two mutual information metrics in signal-dependent interference. Since the target and clutter information are included in the received signal at the beginning of the design, DMI-based waveform is designed according to the following criterion: maximizing the MI between the received signal and target impulse response while minimizing the MI between the received signal and the clutter impulse response. This criterion (...) is equivalent to maximizing the difference between the first MI and the second MI. Then maximizing the difference of two types of MI is used as the objective function, and the optimization model with the transmitted waveform energy constraint is established. In order to solve it, we resort to maximum marginal allocation method to find the DMI-based waveform. Since DMI-based waveform does not allocate energy to the frequency band where the clutter power spectral density is greater than the target PSD, we propose to weight the MI-based waveform and DMI-based waveform to synthesize the final optimal waveform. It could provide different trade-offs between two types of MI. Simulation results show the proposed algorithm is valid. (shrink)

Due to the development of the Chinese economy, the consolidation of national power worldwide, and the increasing frequency of economic and cultural exchanges with foreign countries, the number of people from various countries who travel to China to engage in exchanges has increased significantly. Given the development of economic globalization, the acceleration of the process of educational internationalization represents a general trend in higher education development and a common requirement for universities. In addition to education, international students also experience cross-cultural (...) adaptation, that is, behavioral adaptation or changes that occur in people in response to changes in their home country, whether in the form of external or internal cultural adaptation. For international students, the problem of cross-cultural adaptation not only hinders their learning progress but also affects their psychology and living conditions. This article explains the construction of Habermas’s theory of communication action. According to this theory, the purpose of communication is to coordinate the common actions of actors, and this coordination is achieved through mutual communication, which is mediated by language. The article also discusses the cross-cultural adaptation experienced by international students in Chinese universities and highlights the importance of developing educational services for international students in the context of international education. Studies have shown that female students exhibit slightly worse psychological adaptation than male students and female students have a slightly higher rate of depression rate than male students. An interpersonal study of 120 international students traveling to China found that most of these students were able to adapt in terms of their interpersonal relationships. To solve the problems associated with cross-cultural adaptation of international students in China, some countermeasures have been proposed, mainly including active participation in interpersonal communication, an enhanced understanding of the new culture, and the amplification of cultural identity. (shrink)

If distributed cognition is to become a general analytic frame, it needs to handle more aspects of cognition than just highly efficient problem solving. It should also handle learning. We identify four classes of distributed learning: induction, repurposing, symbiotic tuning, and mutual adaptation. The four classes of distributed learning fit into a two-dimensional space defined by the stability and adaptability of individuals and their environments. In all four classes of learning, people and their environments are highly interdependent during (...) initial learning. At the same time, we present evidence indicating that certain types of interdependence in early learning, most notably mutual adaptation, can help prepare people to be less dependent on their immediate environment and more adaptive when they confront new environments. We also describe and test examples of learning technologies that implement mutual adaptation. (shrink)

Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts’ (natural or didactic) problem‐solving behavior as well as their eye movements to learners. While research on expert‐novice communication mainly focused on experts’ changes in explicit, verbal communication behavior, it is as yet unclear (...) whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts’ natural problem‐solving behavior by contrasting it with that of novices. Then, we explored the changes in experts’ behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts’ automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically. (shrink)

Domain experts regularly teach novice students how to perform a task. This often requires them to adjust their behavior to the less knowledgeable audience and, hence, to behave in a more didactic manner. Eye movement modeling examples (EMMEs) are a contemporary educational tool for displaying experts’ (natural or didactic) problem‐solving behavior as well as their eye movements to learners. While research on expert‐novice communication mainly focused on experts’ changes in explicit, verbal communication behavior, it is as yet unclear (...) whether and how exactly experts adjust their nonverbal behavior. This study first investigated whether and how experts change their eye movements and mouse clicks (that are displayed in EMMEs) when they perform a task naturally versus teach a task didactically. Programming experts and novices initially debugged short computer codes in a natural manner. We first characterized experts’ natural problem‐solving behavior by contrasting it with that of novices. Then, we explored the changes in experts’ behavior when being subsequently instructed to model their task solution didactically. Experts became more similar to novices on measures associated with experts’ automatized processes (i.e., shorter fixation durations, fewer transitions between code and output per click on the run button when behaving didactically). This adaptation might make it easier for novices to follow or imitate the expert behavior. In contrast, experts became less similar to novices for measures associated with more strategic behavior (i.e., code reading linearity, clicks on run button) when behaving didactically. (shrink)

This work examines the importance of distinguishing different levels of psychological explanation and the primacy of the computational level over implementational levels. The framework of levels allows us to recognize the role of formal theories as tools for specifying reasoning tasks at the computational level. It is shown that formal specifications of reasoning tasks allow us to analyze the complexity of the specified tasks and also serve to define reasoning competence and performance errors. Complexity analysis helps us identify tractable, practically (...) significant, subclasses of inference. The identification of these subclasses provides useful ante hoc and post hoc specifications for AI programming projects and psychological modeling. Formalization and complexity analysis also enable us to examine tradeoffs between tractability and range of applicability of implementations of a reasoning task. It is undesirable to obtain tractability at the expense of limiting the applicability of a cognitive mechanism to an unreal situation or a toy domain. It is argued that this undesirable result can be avoided if we examine the structure of the environment in which a mechanism is supposed to work and the environmental assumptions that make the computation tractable. Finally, it is demonstrated that many problems the human mind needs to solve in normal environments are indeed tractable and that the mind is equipped with adaptive mechanisms to solve them efficiently. This demonstration undermines a skeptical challenge to human rationality based on claims that many problems are intractable and that the capacity of the human mind is limited. (shrink)

In association with the development of intermittent renewable energy generation, dynamic multiobjective dispatch faces more challenges for power system operation due to significant REG uncertainty. To tackle the problems, a day-ahead, optimal dispatch problem incorporating energy storage is formulated and solved based on a robust multiobjective optimization method. In the proposed model, dynamic multistage ES and generator dispatch patterns are optimized to reduce the cost and emissions. Specifically, strong constraints of the charging/discharging behaviors of the ES in the space-time (...) domain are considered to prolong its lifetime. Additionally, an adaptive robust model based on minimax multiobjective optimization is formulated to find optimal dispatch solutions adapted to uncertain REG changes. Moreover, an effective optimization algorithm, namely, the hybrid multiobjective Particle Swarm Optimization and Teaching Learning Based Optimization, is employed to seek an optimal Pareto front of the proposed dispatch model. This approach has been tested on power system integrated with wind power and ES. Numerical results reveal that the robust multiobjective dispatch model successfully meets the demands of obtaining solutions when wind power uncertainty is considered. Meanwhile, the comparison results demonstrate the competitive performance of the PSO-TLBO method in solving the proposed dispatch problems. (shrink)

As a NP-hard problem that needs to be solved in real time, the dynamic task allocation problem of unmanned aerial vehicle swarm has gradually become a difficulty and hotspot in the current planning field. Aiming at the problems of poor real-time performance and low quality of the solution in the dynamic task allocation of heterogeneous UAV swarm in uncertain environment, this paper establishes a dynamic task allocation model that can meet the actual needs and uses the binary wolf (...) pack algorithm to solve it, so as to propose a dynamic task allocation method of heterogeneous UAV swarm in uncertain environment. In this method, a dynamic mechanism of attacking while searching and priority attacking of important targets is designed. A dynamic task allocation model of multitarget, multitask, heterogeneous multiaircraft platform and multiconstraint is established based on the target cost-effectiveness ratio and task execution time window. In addition, one-dimensional 0–1 coding method is adopted to encode the task allocation scheme. Furthermore, the wolf pack algorithm is introduced in brief. This paper focuses on the BWPA with the good computational robustness and strong global search ability to solve the dynamic allocation model. According to the simulation results, the designed task allocation method not only has good adaptability to the change of target and UAV number, as well as good stability and scalability, but also can effectively solve the dynamic task allocation problem of heterogeneous UAV swarm in unknown environment. Therefore, the established model and solution method can provide a useful reference for task allocation and other related problems. (shrink)

Open Shop Scheduling Problem is one of the most important scheduling problems in the field of engineering and industry. This kind of problem includes m machines and n jobs, each job contains a certain number of operations, and each operation has a predetermined processing time on its corresponding machine. The order of processing of these operations affects the completion times of all jobs. Therefore, the purpose of OSSP is to achieve a proper order of processing of jobs using (...) specified machines, so that the completion time of all jobs is minimized. In this paper, the strengths and limitations of three methods are evaluated by comparing the results of solving the OSSP in large-scale and small-scale benchmarks. In this case, the minimized completion time and total tardiness are considered the objective functions of the adapted methods. To solve small-scale problems, we adapt a mathematical model called Multiobjective Mixed Linear Programming. To solve large-scale problems, two metaheuristic algorithms including Multiobjective Parallel Genetic Algorithm and Multiobjective Parallel Simulated Annealing are adapted. In experimental results, we randomly generated small-scale problems to compare MOMILP with the Genetic Algorithm and Simulate Annealing. To compare MOPSA and MOPGA with the state of the art and show their strengths and limitations, we use a standard large-scale benchmark. The simulation results of the proposed algorithms show that although the MOPSA algorithm is faster, the MOPGA algorithm is more efficient in achieving optimal solutions for large-scale problems compared with other methods. (shrink)

This paper considers an approach to teaching ethics in bioengineering based on the How People Learn (HPL) framework. Curricula based on this framework have been effective in mathematics and science instruction from the kindergarten to the college levels. This framework is well suited to teaching bioengineering ethics because it helps learners develop “adaptive expertise”. Adaptive expertise refers to the ability to use knowledge and experience in a domain to learn in unanticipated situations. It differs from routine expertise, which (...) requires using knowledge appropriately to solve routine problems. Adaptive expertise is an important educational objective for bioengineers because the regulations and knowledge base in the discipline are likely to change significantly over the course of their careers. This study compares the performance of undergraduate bioengineering students who learned about ethics for stem cell research using the HPL method of instruction to the performance of students who learned following a standard lecture sequence. Both groups learned the factual material equally well, but the HPL group was more prepared to act adaptively when presented with a novel situation. (shrink)

Clark & Thornton's conception finds an echo in implicit learning research, which shows that subjects may perform adaptively in complex structured situations through the use of simple statistical learning mechanisms. However, the authors fail to draw a distinction between, on the one hand, subjects' representations which emerge from type-1 learning mechanisms, and, on the other, their knowledge of the genuine abstract “recoding function” which defines a type-2 problem.

Virtual reality provides an immersive 360-degree viewing experience and has been widely used in many areas. However, the transmission of panoramic video usually places a large demand on bandwidth; thus, it is difficult to ensure a reliable quality of experience under a limited bandwidth. In this paper, we propose a field-of-view prediction methodology based on limited FoV feedback that can fuse the heat map and FoV information to generate a user view. The former is obtained through saliency detection, while the (...) latter is extracted from some user perspectives randomly, and it contains the FoV information of all users. Then, we design a QoE-driven panoramic video streaming system with a client/server architecture, in which the server performs rate adaptation based on the bandwidth and the predicted FoV. We then formulate it as a nonlinear integer programming problem and propose an optimal algorithm that combines the Karush–Kuhn–Tucker conditions with the branch-and-bound method to solve this problem. Finally, we evaluate our system in a simulation environment, and the results show that the system performs better than the baseline. (shrink)

The issue of employability has already become a well-delineated topic of study among interpreting educators. However, the current literature still lacks descriptive research on interpreting students' employability development and ignores the developmental effects of interpreter competences in this process. Moreover, the advantage of using career adaptability for measurement is also under-researched. This exploratory case study aims at taking an initial step forward, surveying interpreting students' career adaptability development and the developmental effects of different interpreter competences on major adaptability resources, and (...) ultimately diagnosing curriculum problems and making modifications accordingly. Thirty grade 2019 interpreting students from three Chinese universities contributed to data collection, through six questionnaires in a two-wave survey. The results highlight that, throughout the Chinese MTI program, interpreting students could become more concerned and well prepared for their future, more curious to explore themselves and their surroundings, and more capable of solving problems. The results also indicate that students' knowledge and language competence serve as the major facilitators in this process, and that other interpreter competences, such as psychological competence, transfer competence, professionalism, and cross-cultural competence, are also instrumental. In order to further boost their adaptability constructs, the results suggest that students' language and knowledge competence, professionalism, and cross-cultural and mental agility still need to be improved. Five suggestions for curriculum revision have been raised accordingly. As an initial effort, the current study will hopefully inspire further studies on interpreting students' career adaptability and add more knowledge to the curriculum design from this viewpoint. (shrink)

The North American wood frog, Rana sylvatica, endures seasonal whole‐body freezing during the winter and thawing during the spring without sustaining any apparent damage from ice or oxidative stress. Strategies from these frogs may solve the shortage of human donor organs, which is a multidisciplinary problem that can be alleviated by eliminating geographical boundaries. Rana sylvatica deploys an array of molecular and physiological responses, such as glucose production and microRNA regulation, to help it survive the cold. These strategies have (...) been adapted in the lab to impart cryotolerance in liver cells, and the non‐freezing supercooled storage of transplantable rat livers − milestones that have advanced the field toward cryopreserving human donor organs in the clinic. In this review, a case is presented for the use of non‐coding RNAs to decrease oxidative damage of donor organs by activating endogenous antioxidant systems prior to procurement. (shrink)

As a class of familiar nonlinear systems, nonaffine systems are frequently encountered in practical applications. Currently, in the context of learning control, there is a lack of research results about such general class of nonlinear systems, especially for the case of performing infinite interval tasks. This article focuses on the incremental adaptive control for nonlinear systems in nonaffine form, without requiring periodicity or repeatability. Instead of using the integral adaptation, incremental adaptive mechanisms are developed and the corresponding control (...) schemes are presented, by which the numerical integration for implementation can be avoided. With the proposed incremental adaptation, the implicit function theorem is introduced to solve the intractability problem of the nonaffine structure. The robustness of the tracking error is characterized, with the aid of a proposed key lemma, while the boundedness of all the variables is examined. Numerical results are presented to verify the effectiveness of the proposed control design. (shrink)

Information plays an important role not only in evolution—genetics can be seen as a mechanism to transfer information from one generation to the next—but also in ecology: virtually all organisms use information about their environment to adjust their behavior and life histories. Indeed, being adapted to something can be defined as having the right information to solve the life-history problems that this creates. It then becomes irrelevant precisely where this information came from (genetics, experience, culture, etc.) but rather becomes an (...) issue of how to assess the fitness value of this information. Here I will explore in some detail the conceptual consequences of the information-based view of evolution. In particular, I will focus on how individuals are actually associations of smaller units that depend on each other’s genetic information and on information from multiple external sources. An important and fundamental problem arises when these different sources of information do not suggest the same adaptations. Conflicting information may thus give new insight into the causes of stress. (shrink)

The puzzle of belief arises as currently no definition captures the various ways in which people believe. As a solution to this puzzle and to make the study of belief empirically tractable, Van Leeuwen and Lombrozo suggest acknowledging the plurality of beliefs and organizing beliefs according to their shared functions and traits. However, their proposal does not make yet the distinction between proper and derived functions of belief‐generating cognitive systems. For that, we need a theoretical perspective anchored in evolutionary thinking. (...) Such a perspective allows us to recognize the adaptive problems belief‐generating cognitive systems solve and what sorts of beliefs they will tend to produce. By analyzing beliefs based on evolutionary considerations, we not only make the puzzle of belief empirically tractable, but also take an important step toward solving it. (shrink)

To understand the possible forms of extraterrestrial intelligence, we need not only astrobiology theories about how life evolves given habitable planets, but also evolutionary psychology theories about how intelligence emerges given life. Wherever intelligent organisms evolve, they are likely to face similar behavioral challenges in their physical and social worlds. The cognitive mechanisms that arise to meet these challenges may then be copied, repurposed, and shaped by further evolutionary selection to deal with more abstract, higher-level cognitive tasks such as conceptual (...) reasoning, symbolic communication, and technological innovation, while retaining traces of the earlier adaptations for solving physical and social problems. These traces of evolutionary pathways may be leveraged to gain insight into the likely cognitive processes of ETIs. We demonstrate such analysis in the domain of search strategies and show its application in the domains of emotional aversions and social/sexual signaling. Knowing the likely evolutionary pathways to intelligence will help us to better search for and process any alien signals from the search for ETIs and to assess the likely benefits, costs, and risks of humans actively messaging ETIs. (shrink)

I propose an adjunct to the two models presented in the target articles, a function of music that is ubiquitous and would have solved a clear adaptive problem, that of transmitting important survival information among pre-literate humans. This class ofknowledge songsuniquely preserved cultural, botanical, medical, safety, and practical information that increased the adaptive fitness of societies.

Multi-Task Learning tries to improve the learning process of different tasks by solving them simultaneously. A popular Multi-Task Learning formulation for SVM is to combine common and task-specific parts. Other approaches rely on using a Graph Laplacian regularizer. Here we propose a combination of these two approaches that can be applied to L1, L2 and LS-SVMs. We also propose an algorithm to iteratively learn the graph adjacency matrix used in the Laplacian regularization. We test our proposal with synthetic and (...) real problems, both in regression and classification settings. When the task structure is present, we show that our model is able to detect it, which leads to better results, and we also show it to be competitive even when this structure is not present. (shrink)

We claim that much of the confusion associated with the "tautology problem" about survival of the fittest is due to the mistake of attributing fitness to individuals instead of to types. We argue further that the problem itself cannot be solved merely by taking fitness as the aggregate cause of reproductive success. We suggest that a satisfying explanation must center not on logical analysis of the concept of general adaptedness but on the empirical analysis of single adapted traits (...) and their causal relationship to changes in allele frequencies. (shrink)

Ultrasonic excitation has been widely used in the detection of microcracks on metal surfaces, but there are problems such as poor excitation effect of ultrasonic pulse, long time to reach the best excitation, and difficult to find microcracks. In this paper, an adaptive ultrasonic pulse excitation device and infrared thermal imaging technology have been combined, as well as their control method, to solve the problem. The adaptive ultrasonic pulse excitation device adds intelligent modules to realize automatic adjustment (...) of detection parameters, which can quickly obtain reliable excitation; the multidegree-of-freedom base realizes the three-dimensional direction change of the ultrasonic gun to adapt to different excitation occasions. When the appropriate ultrasonic excitation makes microcracks in the resonance state, the microcracks can be frictionated, which produce heat rise with the temperature. Then, the microcrack defect can be detected by the infrared thermal instrument through the different surface temperatures with imaging recognition method. Our detection experiments of the titanium alloy plates and the aluminum alloy profiles of marine engineering show that the method can get reliable detection parameters in a short time and measure the crack length effectively. It can be used in many aspects such as crack detection in mechanical structures or complex equipment operating conditions and industrial production processes. (shrink)