Computability logic (CL) is a recently launched program for redeveloping logic as a formal theory of computability, as opposed to the formal theory of truth that logic has more traditionally been. Formulas in it represent computational problems, "truth" means existence of an algorithmic solution, and proofs encode such solutions. Within the line of research devoted to finding axiomatizations for ever more expressive fragments of CL, the present paper introduces a new deductive system CL12 and proves its soundness and completeness with (...) respect to the semantics of CL. Conservatively extending classical predicate calculus and offering considerable additional expressive and deductive power, CL12 presents a reasonable, computationally meaningful, constructive alternative to classical logic as a basis for applied theories. To obtain a model example of such theories, this paper rebuilds the traditional, classical-logic-based Peano arithmetic into a computability-logic-based counterpart. Among the purposes of the present contribution is to provide a starting point for what, as the author wishes to hope, might become a new line of research with a potential of interesting findings—an exploration of the presumably quite unusual metatheory of CL-based arithmetic and other CL-based applied systems. (shrink)

This book deals with a major problem in the study of language: the problem of reference. The ease with which we refer to things in conversation is deceptive. Upon closer scrutiny, it turns out that we hardly ever tell each other explicitly what object we mean, although we expect our interlocutor to discern it. Amichai Kronfeld provides an answer to two questions associated with this: how do we successfully refer, and how can a computer be programmed to achieve this? Beginning (...) with the major theories of reference, Dr Kronfeld provides a consistent philosophical view which is a synthesis of Frege's and Russell's semantic insights with Grice's and Searle's pragmatic theories. This leads to a set of guiding principles, which are then applied to a computational model of referring. The discussion is made accessible to readers from a number of backgrounds: in particular, students and researchers in the areas of computational linguistics, artificial intelligence and the philosophy of language will want to read this book. (shrink)

This dissertation investigates some philosophical issues using computational models. Chapter 1 presents a Lewis-Skyrms signaling game that can exhibit a type of compositionality novel to the signaling game literature. The structure of the signaling game is motivated by an analogy to the alarm calls of putty-nosed monkeys (Cercopithecus nictitans). Putty-nosed monkeys display a compositional system of alarm calls with a semantics that is sensitive to the ordering of terms. This sensitivity to the ordering of terms has not been previously modeled (...) with a Lewis-Skyrms signaling game literature. Signaling games are valued for showing how communicative systems can arise with minimal learning tools. Simulation results show that basic (Roth-Erev) reinforcement learning is sufficient for the acquisition of a compositional signaling system sensitive to the ordering of terms. Chapter 2 investigates social epistemology in the context of an effect of cognitive biases called the illusory truth effect. The illusory truth effect is exhibited when repeated exposure to a statement increases an individual's credence in that statement. While most investigations of the illusory truth effect focus on individuals' belief formation, humans typically form beliefs within a social structure. This is particularly relevant because various social structures can give rise to repeated exposure to statements; e.g. a popular book might recurringly be discussed in one's social circle, or one or two foundational papers might always be cited by a particular lab. So, how does the illusory truth effect influence learning and belief formation in a group? This chapter uses network models to investigate this question. These models show that the illusory truth effect can be very detrimental to a group's belief formation. The effect causes networks to prematurely settle on a belief, in part, through repeated exposure to data points that are not independently generated. Previous research has indicated that the probability of such failures is near zero when networks are large or scientists are forced to explore unpopular and risky science. However, simulation results show that the harmful consequences of the illusory truth effect are robust even in large networks with mandatory exploration. Finally, Chapter 3 shows how a rudimentary type of abstraction can obtain in Lewis-Skyrms signaling games. Here, abstraction is understood as occurring when different particulars take on the same functional role. Some abstraction may be guided by innate biases, and the chapter develops an analogy of reasoning about strategic thinking in chess to highlight some epistemic concerns that are raised by the presentation of abstraction. Concretely, the signaling game models of this chapter are developed in the context of two tasks that are much simpler than strategizing in chess. The first task is a transitive inference task that has been substantially studied in both humans and non-human animals. General features of the models developed for the transitive inference task are then carried over to a model for the second task of learning rudimentary grammatical structures. This second task is based on studies of human infants and non-human primates' ability to learn ``nonsense grammars". Closing discussion highlights some strengths of the abstraction exhibited in the Lewis-Skyrms signaling game models. (shrink)

The spacing effect is among the most widely replicated empirical phenomena in the learning sciences, and its relevance to education and training is readily apparent. Yet successful applications of spacing effect research to education and training is rare. Computational modeling can provide the crucial link between a century of accumulated experimental data on the spacing effect and the emerging interest in using that research to enable adaptive instruction. In this paper, we review relevant literature and identify 10 criteria for rigorously (...) evaluating computational models of the spacing effect. Five relate to evaluating the theoretic adequacy of a model, and five relate to evaluating its application potential. We use these criteria to evaluate a novel computational model of the spacing effect called the Predictive Performance Equation. Predictive Performance Equation combines elements of earlier models of learning and memory including the General Performance Equation, Adaptive Control of Thought—Rational, and the New Theory of Disuse, giving rise to a novel computational account of the spacing effect that performs favorably across the complete sets of theoretic and applied criteria. We implemented two other previously published computational models of the spacing effect and compare them to PPE using the theoretic and applied criteria as guides. (shrink)

This paper proposes two formal models for understanding real-life dialogues, aimed at capturing argumentative structures performatively enacted during conversations. In the course of the investigation, two types of discourse with a high degree of well-structured argumentation were chosen: moral debate and financial communication. The research project found itself confronted by a need to analyse, structure and formally describe large volumes of textual data, where this called for the application of computational tools. It is expected that the results of the proposed (...) research will make a contribution to formal systems modelling and the evaluation of communication from the point of view of argument soundness. (shrink)

A central aim of cognitive science is to understand the fundamental mechanisms that enable humans to navigate and make sense of complex environments. In this letter, we argue that computational complexity theory, a foundational framework for evaluating computational resource requirements, holds significant potential in addressing this challenge. As humans possess limited cognitive resources for processing vast amounts of information, understanding how humans perform complex cognitive tasks requires comprehending the underlying factors that drive information processing demands. Computational complexity theory provides a (...) comprehensive theoretical framework to achieve this goal. By adopting this framework, we can gain new insights into how cognitive systems work and develop a more nuanced understanding of the relation between task complexity and human behavior. We provide empirical evidence supporting our argument and identify several open research questions and challenges in applying computational complexity theory to human decision‐making and cognitive science at large. (shrink)

The present essay includes an overview of key milestones in the development of computer ethics as a field of applied ethics. It also describes the ongoing debate about the proper scope of CE, as a subfield both in applied ethics and computer science. Following a brief description of the cluster of ethical issues that CE scholars and practitioners have generally considered to be the standard or "mainstream" issues comprising the field thus far, the essay speculates about the future (...) direction of CE and describes some theoretical and practical questions that will likely arise. (shrink)

By applying research in artificial intelligence to problems in the philosophy of science, Paul Thagard develops an exciting new approach to the study of scientific reasoning. This approach uses computational ideas to shed light on how scientific theories are discovered, evaluated, and used in explanations. Thagard describes a detailed computational model of problem solving and discovery that provides a conceptually rich yet rigorous alternative to accounts of scientific knowledge based on formal logic, and he uses it to illuminate such topics (...) as the nature of concepts, hypothesis formation, analogy, and theory justification. (shrink)

Only computational explanations of a content‐involving sort can answer certain ‘how’‐questions; can support content‐involving counterfactuals; and have the generality characteristic of psychological explanations. Purely formal characteriza‐tions of computations have none of these properties, and do not determine content. These points apply not only to psychological explanation, but to Turing machines themselves. Computational explanations which involve content are not opposed to naturalism. They are also required if we are to explain the content‐involving properties of mental states.

At its beginnings Humanities Computing was characterized by a primary interest in methodological issues and their epistemological background. Subsequently, Humanities Computing practice has been prevailingly driven by technological developments and the main concern has shifted from content processing to the representation in digital form of documentary sources. The Digital Humanities turn has brought more to the fore artistic and literary practice in direct digital form, as opposed to a supposedly commonplace application of computational methods to scholarly research. As an example (...) of a way back to the original motivations of applied computation in the humanities, a formal model of the interpretive process is here proposed, whose implementation may be contrived through the application of data processing procedures typical of the so called artificial adaptive systems. (shrink)

In the course of consumer behavior, it is necessary to study the relationship between the characteristics of psychological activities and the laws of behavior when consumers acquire and use products or services. With the development of the Internet and mobile terminals, electronic commerce has become an important form of consumption for people. In order to conduct experiential education in E-commerce combined with consumer behavior, courses to understand consumer satisfaction. From the perspective of E-commerce companies, this study proposes to use artificial (...) intelligence image recognition technology to recognize and analyze consumer facial expressions. First, it analyzes the way of human–computer interaction in the context of E-commerce and obtains consumer satisfaction with the product through HCI technology. Then, a deep neural network is used to predict the psychological behavior and consumer psychology of consumers to realize personalized product recommendations. In the course education of consumer behavior, it helps to understand consumer satisfaction and make a reasonable design. The experimental results show that consumers are highly satisfied with the products recommended by the system, and the degree of sanctification reaches 93.2%. It is found that the DNN model can learn consumer behavior rules during evaluation, and its prediction effect is increased by 10% compared with the traditional model, which confirms the effectiveness of the recommendation system under the DNN model. This study provides a reference for consumer psychological behavior analysis based on HCI in the context of AI, which is of great significance to help understand consumer satisfaction in consumer behavior education in the context of E-commerce. (shrink)

``Neural computing'' is a research field based on perceiving the human brain as an information system. This system reads its input continuously via the different senses, encodes data into various biophysical variables such as membrane potentials or neural firing rates, stores information using different kinds of memories (e.g., short-term memory, long-term memory, associative memory), performs some operations called ``computation'', and outputs onto various channels, including motor control commands, decisions, thoughts, and feelings. We show a natural model of neural computing (...) that gives rise to hyper-computation. Rigorous mathematical analysis is applied, explicating our model's exact computational power and how it changes with the change of parameters. Our analog neural network allows for supra-Turing power while keeping track of computational constraints, and thus embeds a possible answer to the superiority of the biological intelligence within the framework of classical computer science. We further propose it as standard in the field of analog computation, functioning in a role similar to that of the universal Turing machine in digital computation. In particular an analog of the Church-Turing thesis of digital computation is stated where the neural network takes place of the Turing machine. (shrink)

The basic motivation behind this work is to tie together various computational complexity classes, whether over different domains such as the naturals or the reals, or whether defined in different manners, via function algebras (Real Recursive Functions) or via Turing Machines (Computable Analysis). We provide general tools for investigating these issues, using two techniques we call approximation and lifting. We use these methods to obtain two main theorems. First, we provide an alternative proof of the result from Campagnolo et al. (...) (J Complex 18:977–1000, 2002), which precisely relates the Kalmar elementary computable functions to a function algebra over the reals. Second, we build on that result to extend a result of Bournez and Hainry (Theor Comput Sci 348(2–3):130–147, 2005), which provided a function algebra for the ${\mathcal{C}}^2$ real elementary computable functions; our result does not require the restriction to ${\mathcal{C}}^2$ functions. In addition to the extension, we provide an alternative approach to the proof. Their proof involves simulating the operation of a Turing Machine using a function algebra. We avoid this simulation, using a technique we call lifting, which allows us to lift the classic result regarding the elementary computable functions to a result on the reals. The two new techniques bring a different perspective to these problems, and furthermore appear more easily applicable to other problems of this sort. (shrink)

In the realm of computational intelligence, the age-old adage, "not everything is black and white," has never been more pertinent. Through the lens of fuzzy logic and neutrosophic systems, Applications of Fuzzy Theory in Applied Sciences and Computer Applications, unravels the complex tapestry of uncertainty, imprecision, and subjectivity in real-world scenarios. This book stands as a testament to the power of fuzzy systems in bridging the gap between theoretical concepts and their pragmatic applications. Chapter one introduces readers to the (...) ever-evolving realm of biometrics, specifically focusing on face recognition. The complexities of human features demand a system that can navigate the nuances, and fuzzy pattern recognition presents a promising solution. Diving deeper into the world of health and demography in Chapter two, the authors explore the potential of fuzzy inference systems in mortality studies. By incorporating a degree of uncertainty, these systems offer a more holistic view of mortality trends and predictions. From biometrics and health, we shift our focus to the mathematical underpinnings of neutrosophic logic in chapter three. Here, the application of neutrosophy over digraphs is meticulously dissected, offering readers an intricate understanding of this unique conjunction. The subsequent chapters delve into various other fields, from reliability analysis and higher education to fisheries and supply chain management, demonstrating the pervasive influence of fuzzy and neutrosophic systems in diverse domains. Chapter t2welve concludes this enlightening journey with a life-altering application - the utilization of fuzzy logic in the detection and classification of brain tumors. Through this chapter, the profound impact of fuzzy systems on healthcare and diagnostics is underscored. This promises a transformative journey, ensuring that by the end, readers will look at uncertainty not as a challenge, but as an opportunity to explore, innovate, and excel. Whether you're a seasoned researcher, a professional seeking innovative solutions, or a curious student, this book has insights to offer to everyone. Welcome to a world where the lines are blurred, but the visions are clear. (shrink)

There has been much debate whether computers can be responsible. This question is usually discussed in terms of personhood and personal characteristics, which a computer may or may not possess. If a computer fulfils the conditions required for agency or personhood, then it can be responsible; otherwise not. This paper suggests a different approach. An analysis of the concept of responsibility shows that it is a social construct of ascription which is only viable in certain social contexts and which serves (...) particular social aims. If this is the main aspect of responsibility then the question whether computers can be responsible no longer hinges on the difficult problem of agency but on the possibly simpler question whether responsibility ascriptions to computers can fulfil social goals. The suggested solution to the question whether computers can be subjects of responsibility is the introduction of a new concept, called “quasi-responsibility” which will emphasise the social aim of responsibility ascription and which can be applied to computers. (shrink)

A number of different uniquenessclaims have been made about computer ethics inorder to justify characterizing it as adistinct subdiscipline of applied ethics. Iconsider several different interpretations ofthese claims and argue, first, that none areplausible and, second, that none provideadequate justification for characterizingcomputer ethics as a distinct subdiscipline ofapplied ethics. Even so, I argue that computerethics shares certain important characteristicswith medical ethics that justifies treatingboth as separate subdisciplines of appliedethics.

Computer simulations are widely used in current scientific practice, as a tool to obtain information about various phenomena. Scientists accordingly rely on the outputs of computer simulations to make statements about the empirical world. In that sense, simulations seem to enable scientists to acquire empirical knowledge. The aim of this paper is to assess whether computer simulations actually allow for the production of empirical knowledge, and how. It provides an epistemological analysis of present-day empirical science, to which the traditional epistemological (...) categories cannot apply in any simple way. Our strategy consists in acknowledging the complexity of scientific practice, and trying to assess its rationality. Hence, while we are careful not to abstract away from the details of scientific practice, our approach is not strictly descriptive: our goal is to state in what conditions empirical science can rely on computer simulations. In order to do so, we need to adopt a renewed epistemological framework, whose categories would enable us to give a finer-grained, and better-fitted analysis of the rationality of scientific practice. (shrink)

Intelligent neurotechnology is an emerging field that combines neurotechnologies like brain-computer interface (BCI) with artificial intelligence. This paper introduces a capability framework to assess the responsible use of intelligent BCI systems and provide practical ethical guidance. It proposes two tests, the threshold and flourishing tests, that BCI applications must meet, and illustrates them in a series of cases. After a brief introduction (Section 1), Section 2 sets forth the capability view and the two tests. It illustrates the threshold test using (...) examples from clinical medicine of BCI applications that enable patients with profound disabilities to function at a threshold level through computer mediation. Section 3 illustrates the flourishing test by exploring possible future applications of BCI involving neuroenhancements for healthy people, using examples adapted from research currently underway in the US military. Section 3 applies a capability lens to a complex case involving dual effects, both therapeutic and non-therapeutic, showing how the threshold and flourishing tests resolve the case. Section 4 replies to three objections: neurorights are the best tool for assessing BCI; the two tests are moving targets; and the analysis utilizes a capability view to do work it is not designed for. The paper concludes that a capability view offers unique advantages and gives practical guidance for evaluating the responsible use of present and future BCI applications. Extrapolating from our analysis may help guide other emerging technologies, such as germline gene editing, expected to impact central human capabilities. (shrink)

Since the sixties, computational modeling has become increasingly important in both the physical and the social sciences, particularly in physics, theoretical biology, sociology, and economics. Sine the eighties, philosophers too have begun to apply computational modeling to questions in logic, epistemology, philosophy of science, philosophy of mind, philosophy of language, philosophy of biology, ethics, and social and political philosophy. This chapter analyzes a selection of interesting examples in some of those areas.

We give a systematic technical exposition of the foundations of the theory of computably compact metric spaces. We discover several new characterizations of computable compactness and apply these characterizations to prove new results in computable analysis and effective topology. We also apply the technique of computable compactness to give new and less combinatorially involved proofs of known results from the literature. Some of these results do not have computable compactness or compact spaces in their statements, and thus these applications are (...) not necessarily direct or expected. (shrink)

Computation and Simulation have always played a role in economics – whether it be pure economic theory or any variant of applied, especially policy-oriented, macro- and microeconomics or what has increasingly come to be called empirical or experimental economics. Computations and simulations are also intrinsically dynamic. This triptych – computation, simulation and dynamic – is given natural foundations, mainly as a result of developments in the mathematics underpinnings in the potentials of computing, using digital technology. A running (...) theme in this essay is the recognition that, increasingly, the development of economic theory seems to go hand in hand with advances in the theory and practice of computing, which is, in turn, a catalyst for the move away from too much reliance on any kind of mathematics for the formalisation of economic entities that is inconsistent with the mathematical, methodological and epistemological foundations of the theory of computation. (shrink)

This article begins with an introduction to defeasible (nonmonotonic) reasoning and a brief description of a computer program, EVID, which can perform such reasoning. I then explain, and illustrate with examples, how this program can be applied in computational representations of ordinary dialogic argumentation. The program represents the beliefs and doubts of the dialoguers, and uses these propositional attitudes, which can include commonsense defeasible inference rules, to infer various changing conclusions as a dialogue progresses. It is proposed that computational (...) representations of this kind are a useful tool in the analysis of dialogic argumentation, and, in particular, demonstrate the important role of defeasible reasoning in everyday arguments using commonsense reasoning. (shrink)

Purpose– This paper aims to demonstrate that computing social issues courses are often being taught by articulating the social impacts of different computer technologies and then applying moral theories to those impacts. It then argues that that approach has a number of serious drawbacks.Design/methodology/approach– A bibliometric analysis of ETHICOMP papers is carried out. Papers from early in the history of ETHICOMP are compared to recent years, so as to determine if papers are more or less focused on social scientific examinations (...) of issues or on ethical evaluations of impacts of technology. The literature is examined to argue the drawbacks of the impact approach.Findings– Over time, ETHICOMP papers have moved away from social scientific examinations of computing to more philosophic and ethical evaluations of perceived impacts of computing. The impact approach has a number of drawbacks. First, it is based on a technological deterministic style of social explanation that has been in disrepute in the academic social sciences for decades. Second, it uses an algorithmic approach to ethics that simplifies the social complexity and uncertainty that is the reality of socio-technological change.Research limitations/implications– The methodology used in this paper is limited in several ways. The bibliometric analysis only examined five years of ETHICOMP papers, while the literature review focused on published computing education research. It is possible that neither of these forms of evidence reflects actual common teaching practice.Practical implications– It is hoped that the arguments in this paper will convince teaching practitioners to modify the way they are teaching computing social issues courses: that is, the authors hope to convince educators to add more focus on the social context of computing.Originality/value– The use of bibliometric analysis in this area is unique. The paper’s argument is perhaps unusual as well. (shrink)

In this commentary, I advocate for strict relations between Marr's levels of analysis. Under a strict relationship, each level is exactly implemented by the subordinate level. This yields two benefits. First, it brings consistency for multilevel explanations. Second, similar to how a sculptor chisels away superfluous marble, a modeler can chisel a computational-level model by applying constraints. By sculpting the model, one restricts the set of possible algorithmic- and implementational-level theories.

The theory of inner functions plays an important role in the study of bounded analytic functions. Inner functions are also useful in applied mathematics. Two foundational results in this theory are Frostman's Theorem and the Factorization Theorem. We prove a uniformly computable version of Frostman's Theorem. We then show that the Factorization Theorem is not uniformly computably true. We then show that for an inner function u with infinitely many zeros, the Blaschke sum of u provides the exact amount (...) of information necessary to compute the factorization of u. Along the way, we prove some uniform computability results for Blaschke products; these results play a key role in the analysis of factorization. We also give some computability results concerning zeros and singularities of analytic functions. We use Type-Two Effectivity as our foundation. (shrink)

Computational techniques comparing co-occurrences of city names in texts allow the relative longitudes and latitudes of cities to be estimated algorithmically. However, these techniques have not been applied to estimate the provenance of artifacts with unknown origins. Here, we estimate the geographic origin of artifacts from the Indus Valley Civilization, applying methods commonly used in cognitive science to the Indus script. We show that these methods can accurately predict the relative locations of archeological sites on the basis of artifacts (...) of known provenance, and we further apply these techniques to determine the most probable excavation sites of four sealings of unknown provenance. These findings suggest that inscription statistics reflect historical interactions among locations in the Indus Valley region, and they illustrate how computational methods can help localize inscribed archeological artifacts of unknown origin. The success of this method offers opportunities for the cognitive sciences in general and for computational anthropology specifically. (shrink)

In the dissertation we study the complexity of generalized quantifiers in natural language. Our perspective is interdisciplinary: we combine philosophical insights with theoretical computer science, experimental cognitive science and linguistic theories. -/- In Chapter 1 we argue for identifying a part of meaning, the so-called referential meaning (model-checking), with algorithms. Moreover, we discuss the influence of computational complexity theory on cognitive tasks. We give some arguments to treat as cognitively tractable only those problems which can be computed in polynomial time. (...) Additionally, we suggest that plausible semantic theories of the everyday fragment of natural language can be formulated in the existential fragment of second-order logic. -/- In Chapter 2 we give an overview of the basic notions of generalized quantifier theory, computability theory, and descriptive complexity theory. -/- In Chapter 3 we prove that PTIME quantifiers are closed under iteration, cumulation and resumption. Next, we discuss the NP-completeness of branching quantifiers. Finally, we show that some Ramsey quantifiers define NP-complete classes of finite models while others stay in PTIME. We also give a sufficient condition for a Ramsey quantifier to be computable in polynomial time. -/- In Chapter 4 we investigate the computational complexity of polyadic lifts expressing various readings of reciprocal sentences with quantified antecedents. We show a dichotomy between these readings: the strong reciprocal reading can create NP-complete constructions, while the weak and the intermediate reciprocal readings do not. Additionally, we argue that this difference should be acknowledged in the Strong Meaning hypothesis. -/- In Chapter 5 we study the definability and complexity of the type-shifting approach to collective quantification in natural language. We show that under reasonable complexity assumptions it is not general enough to cover the semantics of all collective quantifiers in natural language. The type-shifting approach cannot lead outside second-order logic and arguably some collective quantifiers are not expressible in second-order logic. As a result, we argue that algebraic (many-sorted) formalisms dealing with collectivity are more plausible than the type-shifting approach. Moreover, we suggest that some collective quantifiers might not be realized in everyday language due to their high computational complexity. Additionally, we introduce the so-called second-order generalized quantifiers to the study of collective semantics. -/- In Chapter 6 we study the statement known as Hintikka's thesis: that the semantics of sentences like ``Most boys and most girls hate each other'' is not expressible by linear formulae and one needs to use branching quantification. We discuss possible readings of such sentences and come to the conclusion that they are expressible by linear formulae, as opposed to what Hintikka states. Next, we propose empirical evidence confirming our theoretical predictions that these sentences are sometimes interpreted by people as having the conjunctional reading. -/- In Chapter 7 we discuss a computational semantics for monadic quantifiers in natural language. We recall that it can be expressed in terms of finite-state and push-down automata. Then we present and criticize the neurological research building on this model. The discussion leads to a new experimental set-up which provides empirical evidence confirming the complexity predictions of the computational model. We show that the differences in reaction time needed for comprehension of sentences with monadic quantifiers are consistent with the complexity differences predicted by the model. -/- In Chapter 8 we discuss some general open questions and possible directions for future research, e.g., using different measures of complexity, involving game-theory and so on. -/- In general, our research explores, from different perspectives, the advantages of identifying meaning with algorithms and applying computational complexity analysis to semantic issues. It shows the fruitfulness of such an abstract computational approach for linguistics and cognitive science. (shrink)

We apply an algorithmic learning model of inquiry to model reasoning carried by experimental subjects in Wason's _Selection Task_ that represents reasoning in the task as computation of a decision tree that supervenes on semantic representations. We argue that the resulting model improves on previous probabilistic and pragmatic models of the task. In particular, it suggests that subjects' selection could in fact be guided by sophisticated patterns of argumentative reasoning.

The paper considers the intellectual computer mathematics system InparSolver, which is designed to automatically explore and solve basic classes of computational mathematics problems on multi-core computers with graphics accelerators. The problems of results reliability of solving problems with approximate input data are outlined. The features of the use of existing computer mathematics systems are analyzed, their weaknesses are found. The functionality of InparSolver, some innovative approaches to the implementation of effective solutions to problems in a hybrid architecture are described. Examples (...) of applied usage of InparSolver for processes mathematical modeling in various subject areas are given. Nowadays, new more complex objects and phenomena in many subject areas are constantly emerging, which are subject to mathematical research on a computer. This encourages the development of new numerical methods and technologies of mathematical modeling, as well as the creation of more powerful computers for their implementation. With the advent and constant development of supercomputers of various architectures, the problems of their effective use, expansion of tasks range should be solved, ensuring the reliability of computer results and increasing the level of intellectual information support for users ‒ specialists in various fields. Today, the issues of solving these problems are given special attention by many specialists in the fields of information technology and parallel programming. The world's leadingscientists in the field of computer technology see the solution to the problems of efficient usage of modern supercomputers in algorithmic software creation that easily adapts to different computer architectures with different types of memory and coprocessors, supports efficient parallelism on millions of cores etc. In addition, improving the efficiency of high-performance computing on modern supercomputers is provided by their intellectualization, transferring to the computer to perform a significant part of the functions. The industry of development and usage of intelligent computer technologies is one of the main directions of science and technology development in modern society. (shrink)

Classic text considersgeneral theory of computability, computable functions, operations on computable functions, Turing machines self-applied, unsolvable decision problems, applications of general theory, mathematical logic, Kleene hierarchy, computable functionals, classification of unsolvable decision problems and more.

Computational models of infant word‐finding typically operate over transcriptions of infant‐directed speech corpora. It is now possible to test models of word segmentation on speech materials, rather than transcriptions of speech. We propose that such modeling efforts be conducted over the speech of the experimental stimuli used in studies measuring infants' capacity for learning from spoken sentences. Correspondence with infant outcomes in such experiments is an appropriate benchmark for models of infants. We demonstrate such an analysis by applying the DP‐Parser (...) model of Algayres and colleagues to auditory stimuli used in infant psycholinguistic experiments by Pelucchi and colleagues. The DP‐Parser model takes speech as input, and creates multiple overlapping embeddings from each utterance. Prospective words are identified as clusters of similar embedded segments. This allows segmentation of each utterance into possible words, using a dynamic programming method that maximizes the frequency of constituent segments. We show that DP‐Parse mimics American English learners' performance in extracting words from Italian sentences, favoring the segmentation of words with high syllabic transitional probability. This kind of computational analysis over actual stimuli from infant experiments may be helpful in tuning future models to match human performance. (shrink)

This book describes a program of research in computable structure theory. The goal is to find definability conditions corresponding to bounds on complexity which persist under isomorphism. The results apply to familiar kinds of structures (groups, fields, vector spaces, linear orderings Boolean algebras, Abelian p-groups, models of arithmetic). There are many interesting results already, but there are also many natural questions still to be answered. The book is self-contained in that it includes necessary background material from recursion theory (ordinal notations, (...) the hyperarithmetical hierarchy) and model theory (infinitary formulas, consistency properties). (shrink)

Purpose The purpose of this study is to analyze how embedding of self-powered wireless sensors into cloud computing further enables such a system to become a sustainable part of work environment. Design/methodology/approach This is exemplified by an application scenario in healthcare that was developed in the context of the OpSIT project in Germany. A clearly outlined three-layer architecture, in the sense of Internet of Things, is presented. It provides the basis for integrating a broad range of sensors into smart healthcare (...) infrastructure. More specifically, by making use of short-range communication sensors, gateways which implement data transmission and low-level computation and cloud computing for processing the data. Findings A technical in-depth analysis of the first two layers of the infrastructure is given to prove reliability and to determine the communication quality and availability in real-world scenarios. Furthermore, two example use-cases that directly apply to a healthcare environment are examined, concluding with the feasibility of the presented approach. Practical implications Finally, the next research steps, oriented towards the semantic tagging and classification of data received from sensors, and the usage of advanced artificial intelligence-based algorithms on this information to produce useful knowledge, are described together with the derived social benefits. Originality/value The work presents an innovative, extensible and scalable system, proven to be useful in healthcare environments. (shrink)

This study is concerned with processes for discovering new theories in science. It considers a computational approach to scientific discovery, as applied to the discovery of theories in cognitive science. The approach combines two ideas. First, a process-based scientific theory can be represented as a computer program. Second, an evolutionary computational method, genetic programming, allows computer programs to be improved through a process of computational trialand-error. Putting these two ideas together leads to a system that can automatically generate and (...) improve scientific theories. The application of this method to the discovery of theories in cognitive science is examined. Theories are built up from primitive operators. These are contained in a theory language that defines the space of possible theories. An example of a theory generated by this method is described. These results support the idea that scientific discovery can be achieved through a heuristic search process, even for theories involving a sequence of steps. However, this computational approach to scientific discovery does not eliminate the need for human input. Human judgment is needed to make reasonable prior assumptions about the characteristics of operators used in the theory generation process, and to interpret and provide context for the computationally generated theories. (shrink)

We study the computational complexity of the universal and quasi-equational theories of classes of bounded distributive lattices with a negation operation, i.e., a unary operation satisfying a subset of the properties of the Boolean negation. The upper bounds are obtained through the use of partial algebras. The lower bounds are either inherited from the equational theory of bounded distributive lattices or obtained through a reduction of a global satisfiability problem for a suitable system of propositional modal logic.

This article provides a computational example of a mathematical explanation within science, concerning computational equivalence of programs. In addition, it outlines the logical structure of the reasoning involved in explanations in applied mathematics. It concludes with a challenge that the nominalist provide a nominalistic explanation for the computational equivalence of certain programs.

This unique volume introduces and discusses the methods of validating computer simulations in scientific research. The core concepts, strategies, and techniques of validation are explained by an international team of pre-eminent authorities, drawing on expertise from various fields ranging from engineering and the physical sciences to the social sciences and history. The work also offers new and original philosophical perspectives on the validation of simulations. Topics and features: introduces the fundamental concepts and principles related to the validation of computer simulations, (...) and examines philosophical frameworks for thinking about validation; provides an overview of the various strategies and techniques available for validating simulations, as well as the preparatory steps that have to be taken prior to validation; describes commonly used reference points and mathematical frameworks applicable to simulation validation; reviews the legal prescriptions, and the administrative and procedural activities related to simulation validation; presents examples of best practice that demonstrate how methods of validation are applied in various disciplines and with different types of simulation models; covers important practical challenges faced by simulation scientists when applying validation methods and techniques; offers a selection of general philosophical reflections that explore the significance of validation from a broader perspective. This truly interdisciplinary handbook will appeal to a broad audience, from professional scientists spanning all natural and social sciences, to young scholars new to research with computer simulations. Philosophers of science, and methodologists seeking to increase their understanding of simulation validation, will also find much to benefit from in the text. (shrink)

This chapter contains sections titled: Using Nanomaterials Nanotechnology Computing and Robotics Predicting the Future of Technology.

This dissertation examines aspects of the interplay between computing and scientific practice. The appropriate foundational framework for such an endeavour is rather real computability than the classical computability theory. This is so because physical sciences, engineering, and applied mathematics mostly employ functions defined in continuous domains. But, contrary to the case of computation over natural numbers, there is no universally accepted framework for real computation; rather, there are two incompatible approaches --computable analysis and BSS model--, both claiming (...) to formalise algorithmic computation and to offer foundations for scientific computing. The dissertation consists of three parts. In the first part, we examine what notion of 'algorithmic computation' underlies each approach and how it is respectively formalised. It is argued that the very existence of the two rival frameworks indicates that 'algorithm' is not one unique concept in mathematics, but it is used in more than one way. We test this hypothesis for consistency with mathematical practice as well as with key foundational works that aim to define the term. As a result, new connections between certain subfields of mathematics and computer science are drawn, and a distinction between 'algorithms' and 'effective procedures' is proposed. In the second part, we focus on the second goal of the two rival approaches to real computation; namely, to provide foundations for scientific computing. We examine both frameworks in detail, what idealisations they employ, and how they relate to floating-point arithmetic systems used in real computers. We explore limitations and advantages of both frameworks, and answer questions about which one is preferable for computational modelling and which one for addressing general computability issues. In the third part, analog computing and its relation to analogue (physical) modelling in science are investigated. Based on some paradigmatic cases of the former, a certain view about the nature of computation is defended, and the indispensable role of representation in it is emphasized and accounted for. We also propose a novel account of the distinction between analog and digital computation and, based on it, we compare analog computational modelling to physical modelling. It is concluded that the two practices, despite their apparent similarities, are orthogonal. (shrink)

In 2005, IOS Press published the first issue of applied Ontology. At the time, we argued that, at the core of the journal, there was “a desire to understand the nature of reality and how people construe their world”. We declared that ontology was both “fundamental to human thought” and “to translating our thoughts into computational artifacts” (Guarino & Musen,2005). With an editorial board of distinguished scholars representing the fields of computer science, informatics, information science, philosophy, linguistics, psychology, and (...) social science, we had the firm belief that applied Ontologywould fulfill an important academic niche, becoming an essential forum for discussion on topics such as ontological analysis, conceptual modeling, and the role of domain models in building and managing information systems. The facts now show that we were correct. (shrink)

Fodor and others who think that scientific, computational psychology will vindicate commonsense belief-desire psychology have maintained that belief can be identified with the explicit storage of a token with appropriate content. I review and develop problems for the explicit storage view and show that a more plausible account identifies belief with the disposition to use a token with appropriate content in explicit reasoning and planning processes and as a basis for action. I argue that this type of inner disposition account (...) will also apply to most other common sense attitudes. The result is a realism about commonsense belief-desire psychology that is more modest than Fodor's: While such inner dispositions probably do exist, these states will probably not be the main focus of scientific psychological theories. (shrink)

This essay provides a critique of mainstream computer ethics and argues for the importance of a complementary approach called disclosive computer ethics, which is concerned with the moral deciphering of embedded values and norms in computer systems, applications and practices. Also, four key values are proposed as starting points for disclosive studies in computer ethics: justice, autonomy, democracy and privacy. Finally, it is argued that research in disclosive computer ethics should be multi-level and interdisciplinary, distinguishing between a disclosure level, a (...) theoretical level, and an an application level. (shrink)