This paper addresses the selective mechanisms by which criminal proceedings produce strong arguments. It does so by focusing on the failing of argument themes (topoi) in the course of criminal proceedings, rather than on their career. In a further step, the notion of failing is bound to learning: different forms of failing point at different ways and places of learning. The study is comparative, relating cases from four different legal regimes (England, USA, Italy and Germany) that are taken (...) from four extensive ethnographic studies in defense lawyer’s firms. We will track down the failures of topoi at three different stages (pre-trial, trial, and deliberation) in our different legal regimes. Failing occurs in all proceedings in various modes and at different stages. We argue that those modes as well as the different stages at which they occur point at the spots in the respective procedures that allow for learning about the inherent conceptions of “good reasons.”. (shrink)

Based on Kolchinsky and Wolpert’s work on the semantics of autonomous agents, I propose an application of Mathematical Logic and Probability to model cognitive processes. In this work, I will follow Bateson’s insights on the hierarchy of learning in complex organisms and formalize his idea of applying Russell’s Type Theory. Following Weaver’s three levels for the communication problem, I link the Kolchinsky–Wolpert model to Bateson’s insights, and I reach a semantic and conceptual hierarchy in living systems as an explicative (...) model of some adaptive constraints. Due to the generality of Kolchinsky and Wolpert’s hypotheses, I highlight some fundamental gaps between the results in current Artificial Intelligence and the semantic structures in human beings. In light of the consequences of my model, I conclude the paper by proposing a general definition of knowledge in probabilistic terms, overturning de Finetti’s Subjectivist Definition of Probability. (shrink)

Reinforcement learning systems usually assume that a value function is defined over all states (or state-action pairs) that can immediately give the value of a particular state or action. These values are used by a selection mechanism to decide which action to take. In contrast, when humans and animals make decisions, they collect evidence for different alternatives over time and take action only when sufficient evidence has been accumulated. We have previously developed a model of memory processing that includes (...) semantic, episodic and working memory in a comprehensive architecture. Here, we describe how this memory mechanism can support decision making when the alternatives cannot be evaluated based on immediate sensory information alone. Instead we first imagine, and then evaluate a possible future that will result from choosing one of the alternatives. Here we present an extended model that can be used as a model for decision making that depends on accumulating evidence over time, whether that information comes from the sequential attention to different sensory properties or from internal simulation of the consequences of making a particular choice. We show how the new model explains both simple immediate choices, choices that depend on multiple sensory factors and complicated selections between alternatives that require forward looking simulations based on episodic and semantic memory structures. In this framework, vicarious trial and error is explained as an internal simulation that accumulates evidence for a particular choice. We argue that a system like this forms the “missing link” between more traditional ideas of semantic and episodic memory, and the associative nature of reinforcement learning. (shrink)

This is an investigation of the emergence of signaling using one kind of trial and error learning: probe and adjust.Send article to KindleTo send this article to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find (...) out more about sending to your Kindle. Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply. Find out more about the Kindle Personal Document Service.LEARNING TO SIGNAL WITH PROBE AND ADJUSTVolume 9, Issue 2Brian SkyrmsDOI: https://doi.org/10.1017/epi.2012.5Your Kindle email address Please provide your Kindle [email protected]@kindle.com Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Send article to Dropbox To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to Dropbox. LEARNING TO SIGNAL WITH PROBE AND ADJUSTVolume 9, Issue 2Brian SkyrmsDOI: https://doi.org/10.1017/epi.2012.5Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Send article to Google Drive To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to Google Drive. LEARNING TO SIGNAL WITH PROBE AND ADJUSTVolume 9, Issue 2Brian SkyrmsDOI: https://doi.org/10.1017/epi.2012.5Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Export citation Request permission. (shrink)

Using educational robots to integrate computational thinking with cross-disciplinary content has gone beyond Science, Technology, Engineering, and Mathematics, to include foreign-language learning and further cross-context target-language acquisition. Such integration must not solely emphasise CT problem-solving skills. Rather, it must provide students with interactive learning to support their target-language interaction while reducing potential TL anxiety. This study aimed to validate the effects of the proposed method of pair programming along with question-and-response interaction in a board-game activity on young learners’ (...) CT skills and TL learning across contexts. Two Grade 6 classes, one with 16 students who were studying Chinese as a Second Language and the other with 16 students who were studying English as a Foreign Language, participated in the activity. A series of instruments on achievement assessment, questionnaires on CT skills and TL anxiety, and sequential learning behaviour analysis were used to critically examine the results. The main conclusion is that the EFL group showed better social skills of cooperation on CT and lower TL learning anxiety, while the CSL group demonstrated better problem-solving skills in CT, but presented more behaviours of trial-and-error loops. Results not only contribute suggestions for cross-disciplinary learning but also provide support for cross-context instruction beyond educational coursework. (shrink)

This paper draws on the philosophy of Karl Popper to present a descriptive evolutionary epistemology that offers philosophical solutions to the following related problems: ‘What happens when learning takes place?’ and ‘What happens in human learning?’ It provides a detailed analysis of how learning takes place without any direct transfer of information from the environment to the learner, and it significantly extends the author's earlier published work on this topic. She proposes that learning should be construed (...) as a special case of ‘problem solving’ and as a fundamentally critical and creative process in which learning organisms develop ‘expectations’ that are not purely an outcome of genetic inheritance or random mutation. Human learning is then characterised with reference to: objectified knowledge; descriptive and argumentative language; theoretical problems; the search for error and specific limitation. If the author's evolutionary analysis of learning is valid, it would suggest that we should, if we wish to promote learning, be wary of corralling children and older students in environments that inhibit autonomous activity, that discourage criticality and creativity and generally limit opportunities for trial and error‐elimination. But education institutions, particularly those for older children and adolescents, are very often environments of this constraining kind. Traditionally, educationists have vastly underestimated the human potential for imaginative criticism—because in general they have not recognised the extent to which it lies at the heart of what humans, including the youngest children, do in order to succeed at even the most basic tasks. (shrink)

Industry groups engage in venue shifting when they seek to overturn or alter restrictive regulations imposed by one political venue through another. A critical step in this process is resolving uncertainties surrounding the preference of the targeted venue and the nature of the relevant policy proposal. While existing studies emphasize a long-term trial-and-error process of policy learning, we focus on nascent industries and argue that ventures seek other information sources to resolve these uncertainties quickly. In particular, nascent (...) industry groups are likely to perceive that the targeted venue will support their policy proposal if the targeted venue is ideologically distant from the venue that has enacted the restrictive regulations, if the targeted venue has recently supported other nascent industry groups’ similar policy proposals, or if the industry groups themselves are more exposed to industry peers’ success in promoting the same policy proposal in other jurisdictions. Under these conditions, the industry groups invest more to influence the targeted venue in response to restrictive regulations enacted by other venues. We find support for our theory by examining how from 2013 to 2019 the small unmanned aircraft systems industry trade associations in the United States lobbied state governments to nullify local regulations. (shrink)

David Hume’s skeptical solution to the problem of induction was grounded in his belief that we learn by means of custom. We consider here how a form of reinforcement learning like custom may allow an agent to learn how to learn in other ways as well. Specifically, an agent may learn by simple reinforcement to adopt new forms of learning that work better than simple reinforcement in the context of specific tasks. We will consider how such a bootstrapping (...) process may lead to a system that includes trial-and-error forms of learning like win-stay/lose-shift, probe and adjust, and simple reinforcement itself together with higher-rationality inferential tools. (shrink)

Some spatio-temporal structures are easier to transfer implicitly in sequential learning. In this study, we investigated whether the consistent reversal of triads of learned components would support the implicit transfer of their temporal structure in visuomotor sequence learning. A triad comprised three sequential button presses ([1][2][3]) and seven consecutive triads comprised a sequence. Participants learned sequences by trial and error, until they could complete it 20 times without error. Then, they learned another sequence, in which (...) each triad was reversed ([3][2][1]), partially reversed ([2][1][3]), or switched so as not to overlap with the other conditions ([2][3][1] or [3][1][2]). Even when the participants did not notice the alternation rule, the consistent reversal of the temporal structure of each triad led to better implicit transfer; this was confirmed in a subsequent experiment. These results suggest that the implicit transfer of the temporal structure of a learned sequence can be influenced by both the structure and consistency of the change. (shrink)

Brindley proposed that we initially generate movements , under higher cerebral control. As the movement is practiced, the cerebellum learns to link within itself the context in which the movement is made to the lower level movement generators. Marr and Albus proposed that the linkage is established by a special input from the inferior olive, which plays upon an input-output element within the cerebellum during the period of the learning. When the linkage is complete, the occurrence of the context (...) (represented by a certain input to the cerebellum) will trigger (through the cerebellum) the appropriate motor response. The movement is distinguished from the conscious movement by its now being automatic, rapid, and stereotyped. The idea is still controversial, but has been supported by a variety of animal studies and, as reviewed here, is consistent with the results of a number of human PET and ablation studies. I have added to the idea of context-response linkage what I think is another important variable: novel combinations of downstream elements. With regard to the motor system and the muscles, this could explain how varied combinations of muscles may become active in precise time-amplitude specifications so as to produce coordinated movements appropriate to specific contexts. In this target article, I have further extended this idea to the premotor parts of the brain and their role in cognition. These areas receive influences from the cerebellum; they are active both in planning movements that are to be executed and in thinking about movements that are not to be executed. From recent evidence, the cerebellar output extends even to what has been characterized as the ultimate frontal planning area, the cortex, area 46. The cerebellum thus may be involved in context-response linkage, and response combination even at these higher levels. The implication would be that, through practice, an experiential context would automatically evoke a certain mental action plan. The plan would be in the realm of thought, and could lead to execution. The specific cerebellar contribution would be one of the context linkage and the shaping of the response, through trial and error learning. The prefrontal and premotor areas could still plan without the help of the cerebellum, but not so automatically, rapidly, stereotypically, so precisely linked to context, or so free of error. Nor would their activities improve optimally with mental practice. (shrink)

Exploiting the skills of others enables individuals to reduce the risks and costs of resource innovation. Social corvids are known to possess sophisticated social and physical cognitive abilities. However, their capacity for imitative learning and its inter-individual transmission pattern remains mostly unexamined. Here we demonstrate the large-billed crows' ability to learn problem-solving techniques by observation and the dominance-dependent pattern in which this technique is transmitted. Crows were allowed to observe one of two box-opening behaviours performed by a dominant or (...) subordinate demonstrator and then tested regarding action and technique. The observers successfully opened the box on their first attempts by using non-matching actions but matching techniques to those observed, suggesting emulation. In the subsequent test sessions, dominant observers consistently used the learned technique, whereas subordinates learned alternative techniques by explorative trial and error. Our findings demonstrate crows' capacity to learn by observing behaviours and the effect of dominance on transmission patterns of behavioural skills. Keywords: social learning; imitation; emulation; affordance; culture; innovation. (shrink)

Autonomous underwater vehicles are widely used to accomplish various missions in the complex marine environment; the design of a control system for AUVs is particularly difficult due to the high nonlinearity, variations in hydrodynamic coefficients, and external force from ocean currents. In this paper, we propose a controller based on deep reinforcement learning in a simulation environment for studying the control performance of the vectored thruster AUV. RL is an important method of artificial intelligence that can learn behavior through (...) trial-and-error interactions with the environment, so it does not need to provide an accurate AUV control model that is very hard to establish. The proposed RL algorithm only uses the information that can be measured by sensors inside the AUVs as the input parameters, and the outputs of the designed controller are the continuous control actions, which are the commands that are set to the vectored thruster. Moreover, a reward function is developed for deep RL controller considering different factors which actually affect the control accuracy of AUV navigation control. To confirm the algorithm’s effectiveness, a series of simulations are carried out in the designed simulation environment, which is a method to save time and improve efficiency. Simulation results prove the feasibility of the deep RL algorithm applied to the control system for AUV. Furthermore, our work also provides an optional method for robot control problems to deal with improving technology requirements and complicated application environments. (shrink)

Starting with the hypothesis that analogical reasoning consists of a search of semantic space, we used eye-tracking to study the time course of information integration in adults in various formats of analogies. The two main questions we asked were whether adults would follow the same search strategies for different types of analogical problems and levels of complexity and how they would adapt their search to the difficulty of the task. We compared these results to predictions from the literature. Machine (...) class='Hi'>learning techniques, in particular support vector machines (SVMs), processed the data to find out which sets of transitions best predicted the output of a trial (error or correct) or the type of analogy (simple or complex). Results revealed common search patterns, but with local adaptations to the specifics of each type of problem, both in terms of looking-time durations and the number and types of saccades. In general, participants organized their search around source-domain relations that they generalized to the target domain. However, somewhat surprisingly, over the course of the entire trial, their search included, not only semantically related distractors, but also unrelated distractors, depending on the difficulty of the trial. An SVM analysis revealed which types of transitions are able to discriminate between analogy tasks. We discuss these results in light of existing models of analogical reasoning. (shrink)

Two classic learning situations are critically reviewed and interpreted from a synergetic point of view: human learning of complex skills, and animal discrimination learning. Both show typical characteristics of nonlinear phase transitions: instability, fluctuations, critical slowing down and reorganisation. Plateaus in the acquisition curves of complex skills can be viewed as phases of arrested progress in which a reorganisation of simple skills is necessary before their integration into complex units is possible. Fluctuations and critical slowing down are (...) expressed in instances of "vicarious trial-and-error," which describe the oscillating behavior of rats at a choice point that is shown only just before discrimination learning is completed. It is concluded that education might pay more attention to the role of individual learning rhythms. (shrink)

Researchers have long suspected that grapheme-color synaesthesia is useful, but research on its utility has so far focused primarily on episodic memory and perceptual discrimination. Here we ask whether it can be harnessed during rule-based Category learning. Participants learned through trial and error to classify grapheme pairs that were organized into categories on the basis of their associated synaesthetic colors. The performance of synaesthetes was similar to non-synaesthetes viewing graphemes that were physically colored in the same way. (...) Specifically, synaesthetes learned to categorize stimuli effectively, they were able to transfer this learning to novel stimuli, and they falsely recognized grapheme-pair foils, all like non-synaesthetes viewing colored graphemes. These findings demonstrate that synaesthesia can be exploited when learning the kind of material taught in many classroom settings. (shrink)

Sequence learning is fundamental to a wide range of cognitive functions. Explaining how sequences—and the relations between the elements they comprise—are learned is a fundamental challenge to cognitive science. However, although hundreds of articles addressing this question are published each year, the actual learning mechanisms involved in the learning of sequences are rarely investigated. We present three experiments that seek to examine these mechanisms during a typing task. Experiments 1 and 2 tested learning during typing single (...) letters on each trial. Experiment 3 tested for “chunking” of these letters into “words.” The results of these experiments were used to examine the mechanisms that could best account for them, with a focus on two particular proposals: statistical transitional probability learning and discriminative error-driven learning. Experiments 1 and 2 showed that error-driven learning was a better predictor of response latencies than either n-gram frequencies or transitional probabilities. No evidence for chunking was found in Experiment 3, probably due to interspersing visual cues with the motor response. In addition, learning occurred across a greater distance in Experiment 1 than Experiment 2, suggesting that the greater predictability that comes with increased structure leads to greater learnability. These results shed new light on the mechanism responsible for sequence learning. Despite the widely held assumption that transitional probability learning is essential to this process, the present results suggest instead that the sequences are learned through a process of discriminative learning, involving prediction and feedback from prediction error. (shrink)

Epistemic warrant consists in the normal functioning of the belief-forming process when the process has forming true beliefs reliably as an etiological function. Evolution by natural selection is the most familiar source of etiological functions. . What then of learning? What then of Swampman? Though functions require history, natural selection is not the only source. Self-repair and trial-and-error learning are both sources. Warrant requires history, but not necessarily that much.

Based on instructions people can form task representations that shield relevant from seemingly irrelevant information. It has been documented that instructions can tie people to a particular way of performing a task despite that in principle a more efficient way could be learned and used. Since task shielding can lead to persistence of inefficient variants of task performance, it is relevant to test whether individuals with attention deficit/hyperactivity disorder – characterized by less task shielding – are more likely and quicker (...) to escape a suboptimal instructed variant of performing a task. The paradigm used in this online study builds on the observation that in many environments different covarying features could be used to determine the appropriate response. For instance, as they approach a traffic light, drivers and pedestrians monitor the color and/or the position of the signal. Similarly, we instructed participants to respond to the color of a stimulus without mentioning that color covaried with the position of the stimulus. In order to assess whether with practice participants would use the non-instructed feature position to an increasing extent, we compared reaction times and error rates for standard trials to trials in which color was either ambiguous or did not match the usual covariation. Results showed that the covariation learning task can be administered online to adult participants with and without ADHD. Performance differences suggested that with practice ADHD participants might increase attention to non-instructed stimulus features. Yet, they used the non-instructed covarying stimulus feature to a similar extent as other participants. Together the results suggest that participants with ADHD do not lag behind in abandoning instructed task processing in favor of a learned alternative strategy. (shrink)

ExtractBrian Skyrms's Signals has the virtues familiar from his Evolution of the Social Contract and The Stag Hunt. He begins with a very simple model of agents in interaction, and in a series of brief and beautifully clear chapters, this model and its successors are explored, elaborated, connected and illustrated through biological theory and the social sciences. Signals borrows its core model from David Lewis: it is Lewis's signalling game. In this game, two agents interact. One agent can observe which (...) of two equi-probable states the world is in, but that agent cannot act directly and profitably on that information. However, the informed agent can act in a way that will be perceptually salient to a second agent: say, by raising a red or a green flag. The second agent does have the capacity to respond appropriately to each state of the world. If that second agent chooses the right option, given the state of the world, both are rewarded. If the second agent fails to choose the right action, neither are. Obviously, the two agents are best off if they have a practice in which the informed agent regularly chooses a distinct, salient cue in response to each of the two world states, and in which the powerful agent uses that cue to select the rewarding act. Less obviously, agents with simple trial and error learning capacities can learn to signal and respond: neither explicit negotiation nor cognitive sophistication are required. Likewise, if individual agents do not have the capacity to learn, but if they breed true but with some variation, the evolutionary version of trial and error learning can take a population to one of the signalling system equilibria. View HTML Send article to KindleTo send this article to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle. Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply. Find out more about the Kindle Personal Document Service.A GLASS HALF-FULL: BRIAN SKYRMS'S SIGNALSVolume 28, Issue 1Kim Sterelny DOI: https://doi.org/10.1017/S0266267112000120Your Kindle email address Please provide your Kindle [email protected]@kindle.com Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Send article to Dropbox To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to Dropbox. A GLASS HALF-FULL: BRIAN SKYRMS'S SIGNALSVolume 28, Issue 1Kim Sterelny DOI: https://doi.org/10.1017/S0266267112000120Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Send article to Google Drive To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to Google Drive. A GLASS HALF-FULL: BRIAN SKYRMS'S SIGNALSVolume 28, Issue 1Kim Sterelny DOI: https://doi.org/10.1017/S0266267112000120Available formats PDF Please select a format to send. By using this service, you agree that you will only keep articles for personal use, and will not openly distribute them via Dropbox, Google Drive or other file sharing services. Please confirm that you accept the terms of use. Cancel Send ×Export citation Request permission. (shrink)

Classification learning is a preeminent human ability within the animal kingdom but the key mechanisms of brain networks regulating learning remain mostly elusive. Recent neuroimaging advancements have depicted human brain as a complex graph machinery where brain regions are nodes and coherent activities among them represent the functional connections. While long-term motor memories have been found to alter functional connectivity in the resting human brain, a graph topological investigation of the short-time effects of learning are still not (...) widely investigated. For instance, classification learning is known to orchestrate rapid modulation of diverse memory systems like short-term and visual working memories but how the brain functional connectome accommodates such modulations is unclear. We used publicly available repositories (openfmri.org) selecting three experiments, two focused on short-term classification learning along two consecutive runs where learning was promoted by trial-by-trial feedback errors, while a further experiment was used as supplementary control. We analyzed the functional connectivity extracted from BOLD fMRI signals, and estimated the graph information processing in the cerebral networks. The information processing capability, characterized by complex network statistics, significantly improved over runs, together with the subject classification accuracy. Instead, null-learning experiments, where feedbacks came with poor consistency, did not provoke any significant change in the functional connectivity over runs. We propose that learning induces fast modifications in the overall brain network dynamics, definitely ameliorating the short-term potential of the brain to process and integrate information, a dynamic consistently orchestrated by modulations of the functional connections among specific brain regions. (shrink)

This guide accompanies the following article(s): ‘Full Disclosure of the “Raw Data” of Research on Humans: Citizens’ Rights, Product Manufacturer’s Obligations and the Quality of the Scientific Database.’Philosophy Compass 6/2 (2011): 90–99. doi: 10.1111/j.1747‐9991.2010.00376.x Author’s Introduction Securing consent (and informed consent) from patients and research study participants is a key concern in patient care and research on humans. Yet, the legal doctrines of consent and informed consent differ in their applications. In patient care, the judicial doctrines of consent and informed (...) consent are disclosure doctrines based on the obligation of physicians to inform their patients of the following types of information: the nature of the procedure the physician is recommending in the patent’s care (P), the alternatives to the physician‐recommendation (A), and the risks of procedure and its alternatives (R). In addition, the physician must provide truthful answers to the patient’s questions (Q) to the best of the physician’s abilities. In research on humans, the onus of disclosure by study sponsors and principal investigators is much greater than in patient care precisely because the purpose of research is not patient care. The purpose of research is the identification and development of new generalizable knowledge. Thus, participation in a research study or trial may not benefit the study volunteer at all. In addition, the participant may carry a heavy risk burden in relationship to any testing of a newly designed drug or device as part of their experiences in the research study. Presently, despite the risks borne by the research study participant, the raw data collected from volunteers in research trials are treated by courts as if they were the private property of the study sponsor rather than generally owed to the public as would be expected by an effort like research participation aimed at contributing to the development of generalizable knowledge. This paper reviews the obligations that study sponsors owe to their study participants based on the very definition of research as a systematic activity whose purpose is to develop generalizable knowledge to help all humans. Author Recommends Court cases Canterbury v. Spence, United States Court of Appeals, District of Columbia Circuit 464 F.2d 772 (1972). (Federal appellate decision heard in the District of Columbia, USA) Reibl v. Hughes, 2 S.C.R. 880 (1980). (Supreme Court of Canada) Rogers v. Whitaker, 175 C.L. R. 479 (1992). (High Court of Australia) Sidaway v. Board of Governors of the Bethlem Royal Hospital and the Maudsley Hospital and Others. 1 A.C. 871 (1985) (House of Lords) Canterbury v. Spence is the landmark Federal informed consent case in the United States heard in the District of Columbia. In this case, Judge Spottswood Robinson articulated the reasonable person standard of informed consent. This standard was subsequently adopted by the Supreme Court of Canada (Reibl v. Hughes, 2 S.C.R. 880 (1980)) and the High Court of Australia (Rogers v. Whitaker, 175 C.L. R. 479 (1992)). The House of Lords rejected the reasonable person standard in England in Sidaway v. Board of Governors of the Bethlem Royal Hospital and the Maudsley Hospital and Others. 1 A.C. 871 (1985). Book Mazur, Dennis J. The Science and Ethics of Research on Humans. Baltimore, MD: Johns Hopkins University Press, 2007. This book is a detailed guide for the review of scientific and ethical aspects of research on humans contained in the research study protocols and research informed consent forms which need to be submitted by study sponsors and principal investigators to institutional review boards (IRBs) for IRB review before a research study can receive approval to be conducted within a human study population in those institutions over which the IRB has authority. It also presents basic definitions in the area of research on humans and basic approaches to help conduct a deep review of the underlying scientific and ethical issues that are present within a research study protocol and its accompanying research informed consent form. Report National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. The Belmont Report: Ethical Guidelines for the Protection of Human Subjects of Research. Washington, DC: DHEW Publications, 1978 (78‐0012). This U.S. National Commission in the Belmont Report argued for the necessity of a reasonable volunteer standard in research on humans in the United States. Arguing that the professional standard and the reasonable person standard of consent and informed consent were insufficient to base a disclosure standard in research on humans, this National Commission developed the reasonable volunteer standard where a study participant is to be approached in research informed consent with that information that a reasonable volunteer would want to know. Online Materials Belmont Report: Syllabus Topics for Lecture and Discussion Week I: Introduction and Overview Readings: Rogers v. Whitaker, 175 C.L.R. 479 (1992). (High Court of Australia) Sidaway v. Board of Governors of the Bethlem Royal Hospital and the Maudsley Hospital and Others. 1 A.C. 871 (1985) (House of Lords) Week II: The Different Standards of Consent and Informed Consent Readings: Canterbury v. Spence, 464 F.2d 772 (1972). (Federal appellate opinion heard in the District of Columbia) Sidaway v. Board of Governors of the Bethlem Royal Hospital and the Maudsley Hospital and Others. 1 A.C. 871 (1985) (House of Lords) Week III: Definition of Research Reading: Mazur, Dennis J. The Science and Ethics of Research on Humans. Baltimore, MD: Johns Hopkins University Press, 2007. (Especially Chapters 2 and 3) Week IV: How to Review a Research Study Protocol and Research Informed Consent Form Reading: Mazur, Dennis J. The Science and Ethics of Research on Humans. Baltimore, MD: Johns Hopkins University Press, 2007. (Especially Chapters 4–6, 10, and 12–14) Week V: Obligations in Research of Humans Versus Patient Care Reading: National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. The Belmont Report: Ethical Guidelines for the Protection of Human Subjects of Research. Washington, DC: DHEW Publications, 1978 (78‐0012). Focus Questions • How do the judicial doctrines of consent in England and Australia compare to the judicial doctrines of informed consent in the United States and Canada? • How does a professional standard of disclosure differ from a reasonable person standard of disclosure? • What is the definition of research? • How is a research study (study proposal and research informed consent form) reviewed from scientific and ethical bases for considerations of approval by an IRB? • How do the obligations of a study sponsor, a principal investigator, and a research team conducting a research trial on human study participants differ from the obligations of a physician caring for a patient? • Should all raw data of research derived from humans be made available to the public for use in developing generalizable knowledge to help others, or should raw data be considered the private property of the study sponsors (for example, prescription drug manufacturers), who fund the research trials? Seminar/project Idea Draw a timeline of the development of the basic concepts of consent and informed consent in patient care and in patient research. On this timeline, first place the dates of the key court cases in England, the United States, Canada, and Australia on consent and informed consent. Then place the date of the development of the Belmont Report. Why do differences exist between these four countries in terms of the legal requirements of informedness of a patient (in medical care) and a study participant (in medical research)? What roles if any do the concepts of self‐determination and self‐decision have in consent and informed consent in patient care and in informed consent in research on humans among the four countries of interest? What are the realities of research on human participants that require a new standard of informed consent, the reasonable volunteer standard, to be developed beyond the two standards in patient care, the professional standard, and the reasonable person standard? Counterpoint Arguments The following are counterpoint arguments that need to be appreciated to more fully understand the concepts that impact the thesis that ‘raw data’ should be open to the public to allow the opportunity of checking of the results of its associated scientific paper and for further analysis. De‐Identified (Anonymized) Raw Data A current approach to identifying (anonymizinig) raw data is based on the Health Insurance Portability and Accountability Act (HIPAA) of 1996 (P.L.104‐191). HIPAA was enacted by the U.S. Congress in 1996 to keep a person’s medical information private. In a research study, a person’s private medical information can become research data. HIPAA’s Privacy Rule allows a covered entity to de‐identify data by removing all 18 elements that could be used to identify the individual or the individual’s relatives, employers, or household members; these elements are enumerated in the Privacy Rule. The covered entity must also have no actual knowledge that the remaining information could be used alone or in combination with other information to identify the individual who is the subject of the information. Under this method, the identifiers that must be removed are the following: 1 Names. 2 All geographic subdivisions smaller than a state, including street address, city, county, precinct, ZIP Code, and their equivalent geographical codes, except for the initial three digits of a ZIP Code if, according to the current publicly available data from the Bureau of the Census: 2a. The geographic unit formed by combining all ZIP Codes with the same three initial digits contains more than 20,000 people. 2b. The initial three digits of a ZIP Code for all such geographic units containing 20,000 or fewer people are changed to 000. 3 All elements of dates (except year) for dates directly related to an individual, including birth date, admission date, discharge date, and date of death, and all ages over 89 and all elements of dates (including year) indicative of such age, except that such ages and elements may be aggregated into a single category of age 90 or older. 4 Telephone numbers. 5 Facsimile numbers. 6 Electronic mail addresses. 7 Social security numbers. 8 Medical record numbers. 9 Health plan beneficiary numbers. 10 Account numbers. 11 Certificate/license numbers. 12 Vehicle identifiers and serial numbers, including license plate numbers. 13 Device identifiers and serial numbers. 14 Web universal resource locators (URLs). 15 Internet protocol (IP) address numbers. 16 Biometric identifiers, including fingerprints and voiceprints. 17 Full‐face photographic images and any comparable images. 18 Any other unique identifying number, characteristic, or code, unless otherwise permitted by the Privacy Rule for re‐identification. Even though ‘raw data’ can be de‐identified (anonymized) so that there is no way to trace back the data to the study participant from which it was drawn, there are still questions whether the ‘de‐identified raw data’ can be given to other researchers or made public without the original study participant’s approval. It may be the case that this approval could be done at the start of any research study where the individual considering study participation would be counseled on what the process of de‐identification consists of and would be asked whether the participant would allow use of the data by other researchers or made available to the public in a de‐identified state. However, there may be questions of the study participants as to whether the data are truly de‐identified and untraceable back to the study participant since the participant would not be able to see the process actually being carried out in detail in all relevant circumstances. Using Raw Data in Context Simply being in possession of raw data is never enough to build on that data from a research perspective. Researchers need to understand the context of the scientific research study in which the data were collected. This research context includes (but is not limited to): (i) the scientific hypothesis of the research study, (ii) the inclusion and exclusion criteria selected by the research designers of the study to determine which study participants were included and which were excluded from the study, (iii) the methods used to collect the data and possibilities of errors in the data collection processes, and (iv) answers to questions regarding whether any data were excluded from the study data and why these data were excluded. Ownership Rights Over Data There are ownership rights over data. Ownership rights include court decision making related to the question which parties are to be considered as the owners of the data. Possible owners here include (but are not limited to) (i) the study sponsor whose only role was to fund that study, (ii) the principal investigator(s) who developed the scientific hypothesis, and (iii) individual study participants through special contracts made by individual participants who negotiate such contracts with study sponsors and principal investigators to share in the ownership of data. Examples of such data are participant sources of unique gene lines or unique cell lines to be used in future research. Objections to Data Sharing Finally, individual researchers may simply object to sharing data. A researcher’s arguments here may be simply stating that he or she has a right to fully analyze the data since the collection of the data was the researchers’ idea in the first place. These researchers may argue that they have the right to mine the data as fully as they can before deciding to make the data open to the public for others to analyze. Works Cited 1 Kaiser, J. ‘Making Clinical Data Widely Available.’Science 322.5899 (10 Oct. 2008): 217–8. 2 de Lusignan, S., J.F. Metsemakers, P. Houwink, V. Gunnarsdottir, and J. van der Lei. ‘Routinely Collected General Practice Data: Goldmines for Research? A Report of the European Federation for Medical Informatics Primary Care Informatics Working Group (EFMI PCIWG) from MIE2006, Maastricht, The Netherlands.’Informatics in Primary Care 14.3 (2006): 203–9. 3 Sim, I. ‘Human Studies Database Project’, CTSA Data Repositories Symposium (17 Oct. 2008). 23 Nov. 2010. 4 Sim, I., C.G. Chute, H. Lehmann, R. Nagarajan, M. Nahm, and R.H. Scheuermann. ‘Keeping Raw Data in Context.’Science 323.5915 (6 Feb. 2009): 713. 5 U.S. Department of Health and Human Services, National Institutes of Health, HIPAA Privacy Rule, Information for Researchers. 13 Nov. 2010. 6 Wilczynski, N.L., R.B. Haynes, and Hedges Team. ‘EMBASE Search Strategies for Identifying Methodologically Sound Diagnostic Studies for Use by Clinicians and Researchers.’BMC Medicine 29.3 (March 2005): 7. (shrink)

Byrne & Russon propose that priming can account for the imitation of simple actions, but they fail to explain how the behavior of another can prime the observer's own behavior. They also propose that imitation of complex skills requires a sequence of acts tied together by a program, but they fail to rule out the role of trial-and-error learning and perceptual/motivational mechanisms in such task acquisition.

Despite being a staple of liberal-democratic politicians’ and theorists’ rhetorical arsenal, ‘openness’ as a political commitment has yet to receive sustained philosophical analysis. My aim in this paper is to provide such an analysis. I will argue that political openness involves a readiness by an agent to engage with others forthrightly and receptively, and to recognise their authoritative standing in political domains. I demonstrate the explanatory value of this account by showing that it provides an insightful explanation of what’s at (...) stake in the emerging political cleavage between ‘open’ and ‘closed’ politics, explains the appeal of ‘the open society’ as an epithet for liberal democracies, and provides a compelling interpretation of openness’ contribution to social dynamism and progressive reform, one which diverges favourably from the emphasis others have put on social experimentation and trial and error learning. (shrink)

The large scale, time varying, and diversification of physically coupled networked infrastructures such as power grid and transportation system lead to the complexity of their controller design, implementation, and expansion. For tackling these challenges, we suggest an online distributed reinforcement learning control algorithm with the one-layer neural network for each subsystem or called agents to adapt the variation of the networked infrastructures. Each controller includes a critic network and action network for approximating strategy utility function and desired control law, (...) respectively. For avoiding a large number of trials and improving the stability, the training of action network introduces supervised learning mechanisms into reduction of long-term cost. The stability of the control system with learning algorithm is analyzed; the upper bound of the tracking error and neural network weights are also estimated. The effectiveness of our proposed controller is illustrated in the simulation; the results indicate the stability under communication delay and disturbances as well. (shrink)

This essay argues that there can be a duty to obey the law when it is produced by the evolutionary forces at work in the customary and common law. Human beings' inherent epistemic limitations mean that they must rely on the trial and error learning built into the common law process to discover rules that facilitate peaceful social interaction. Hence, a duty to obey the law produced by the common law process can arise from individuals' natural duty (...) to promote social peace. This argument cannot be extended to ground political obligation. It does not give rise to a duty to obey the state. (shrink)

What language allows us to do is to "steal" categories quickly and effortlessly through hearsay instead of having to earn them the hard way, through risky and time-consuming sensorimotor "toil" (trial-and-error learning, guided by corrective feedback from the consequences of miscategorisation). To make such linguistic "theft" possible, however, some, at least, of the denoting symbols of language must first be grounded in categories that have been earned through sensorimotor toil (or else in categories that have already been (...) "prepared" for us through Darwinian theft by the genes of our ancestors); it cannot be linguistic theft all the way down. The symbols that denote categories must be grounded in the capacity to sort, label and interact with the proximal sensorimotor projections of their distal category-members in a way that coheres systematically with their semantic interpretations, both for individual symbols, and for symbols strung together to express truth-value-bearing propositions. (shrink)

This paper is part of a project that is based on the notion of a dialectical system, introduced by Magari as a way of capturing trial and error mathematics. In Amidei et al. (2016, Rev. Symb. Logic, 9, 1–26) and Amidei et al. (2016, Rev. Symb. Logic, 9, 299–324), we investigated the expressive and computational power of dialectical systems, and we compared them to a new class of systems, that of quasi-dialectical systems, that enrich Magari’s systems with a (...) natural mechanism of revision. In the present paper we consider a third class of systems, that of p-dialectical systems, that naturally combine features coming from the two other cases. We prove several results about p-dialectical systems and the sets that they represent. Then we focus on the completions of first-order theories. In doing so, we consider systems with connectives, i.e. systems that encode the rules of classical logic. We show that any consistent system with connectives represents the completion of a given theory. We prove that dialectical and q-dialectical systems coincide with respect to the completions that they can represent. Yet, p-dialectical systems are more powerful; we exhibit a p-dialectical system representing a completion of Peano Arithmetic that is neither dialectical nor q-dialectical. (shrink)

Banded geckos (Coleonyx variegatus) were trained, at the rate of five daily trials, on eight intradimensional spatial shifts to a criterion of 80% correct per reversal. In contrast to several previously reported failures to obtain reversal learning, Coleonyx demonstrated significant improvement on both errors and trials to criterion. Their reversal performance compares favorably with that of birds and mammals and a common index of reversal ability, the mean total error, did not differentiate between taxa.

Harry Harlow is credited with the discovery of learning set, a process whereby problem solving becomes essentially complete in a single trial of training. Harlow described that process as one that freed his primates from arduous trial-and-error learning. The capacity of the learner to acquire learning sets was in positive association with the complexity and maturation of their brains. It is here argued that Harlow's successful conveyance of learning-set phenomena is of historic significance (...) to the philosophy of psychology. Learning set is said to reflect the affirmation or rejection of hypotheses. Hypotheses are generated by the learner's brain, not its muscles. Thus, learning-set research served to advance the perspective that even nonhuman primates think and that their thinking reflects the active processing of information accrued from efforts to solve problems. Their learning processes are not simply the strengthening of some motor responses over others. Hence, learning-set research served to advance studies of animals as rational agents. This trend is serving to supplant the radical-behavioristic models, formulated earlier this century, with models predicated on rational processes for animals' complex learning and behavior. (shrink)