Modularity theorists have challenged that there are, or could be, general learning mechanisms that explain theory-of-mind development. In response, supporters of the ‘scientific theory-theory’ account of theory-of-mind development have appealed to children's use of auxiliary hypotheses and probabilistic causal modeling. This article argues that these general learning mechanisms are not sufficient to meet the modularist's challenge. The article then explores an alternative domain-general learning mechanism by proposing that children grasp the concept belief through the progressive alignment of relational structure that (...) occurs as a result of structural-comparison. The article also explores the implications of the proposed account for Fodor's puzzle of conceptual learning. (shrink)

The ability to make informative comparisons is central to human cognition. Comparison involves aligning two representations and placing their elements into correspondence. Detecting correspondences is a necessary component of analogical inference, recognition, categorization, schema formation, and similarity judgment. Connectionist Analogy Builder (CAB) determines correspondences through a simple iterative computation that matches elements in one representation with elements playing compatible roles in the other representation while simultaneously enforcing structural constraints. CAB shows promise as a process model of comparison as its performance (...) can be related to human performance (e.g., solution trajectory, error patterns, time‐on‐task). Furthermore, CAB's bounded working memory allows it to account for the inherent capacity limitations of human processing. CAB's strengths are its parsimony, transparency of operations, and ability to generate performance predictions. In this paper, CAB is evaluated against benchmark phenomena from the analogy literature. (shrink)

Analogical cognition refers to the ability to detect, process, and learn from relational similarities. The study of analogical and similarity cognition is widely considered one of the ‘success stories’ of cognitive science, exhibiting convergence across many disciplines on foundational questions. Given the centrality of analogy to mind and knowledge, it would benefit philosophers investigating topics in epistemology and the philosophies of mind and language to become familiar with empirical models of analogical cognition. The goal of this essay is to describe (...) recent empirical work on analogical cognition as well as model applications to philosophical topics. Topics to be discussed include the epistemological distinction between implicit knowledge and explicit knowledge, the debate between empiricists and nativists, the frame problem, expertise, creativity and autism, cognitive architecture, and relational knowledge. Particular attention is given to Dedre Gentner and colleague’s structure-mapping theory – the most developed and widely accepted model of analogical cognition. (shrink)

Abstract How do people find arguments while engaged in a discussion? Following an analogy with visual search, a mechanism that performs this task is described. It is a metarepresentational device that examines representations in a mostly serial manner until it finds a good enough argument supporting one’s position. It is argued that the mechanism described in dual process theories as ‘system 2’, or analytic reasoning fulfills these requirements. This provides support for the hypothesis that reasoning serves an argumentative function. Content (...) Type Journal Article Pages 1-20 DOI 10.1007/s10503-011-9256-1 Authors Hugo Mercier, Philosophy, Politics and Economics Program, University of Pennsylvania, 313 Cohen Hall, 249 South 36th Street, Philadelphia, PA 19104, USA Journal Argumentation Online ISSN 1572-8374 Print ISSN 0920-427X. (shrink)

Laboratory-based studies of problem solving suggest that transfer of solution principles from an analogue to a target arises only minimally without the presence of directive hints. Recently, however, real-world studies indicate that experts frequently and spontaneously use analogies in domain-based problem solving. There is also some evidence that in certain circumstances domain novices can draw analogies designed to illustrate arguments. It is less clear, however, whether domain novices can invoke analogies in the sophisticated manner of experts to enable them to (...) progress problem solving. In the current study groups of novices and experts tackled large-scale management problems. Spontaneous analogising was observed in both conditions, with no marked differences between expertise levels in the frequency, structure, or function of analogising. On average four analogies were generated by groups per hour, with significantly more relational mappings between analogue and target being produced than superficial object-and-attribute mappings. Analogising served two different purposes: problem solving (dominated by relational mappings), and illustration (which for novices was dominated by object-and-attribute mappings). Overall, our novices showed a sophistication in domain-based analogical reasoning that is usually only observed with experts, in addition to a sensitivity to the pragmatics of analogy use. (shrink)

Prior to the twentieth century, theories of knowledge were inherently perceptual. Since then, developments in logic, statis- tics, and programming languages have inspired amodal theories that rest on principles fundamentally different from those underlying perception. In addition, perceptual approaches have become widely viewed as untenable because they are assumed to implement record- ing systems, not conceptual systems. A perceptual theory of knowledge is developed here in the context of current cognitive science and neuroscience. During perceptual experience, association areas in the (...) brain capture bottom-up patterns of activation in sensory-motor areas. Later, in a top-down manner, association areas partially reactivate sensory-motor areas to implement perceptual symbols. The stor- age and reactivation of perceptual symbols operates at the level of perceptual components – not at the level of holistic perceptual expe- riences. Through the use of selective attention, schematic representations of perceptual components are extracted from experience and stored in memory (e.g., individual memories of green, purr, hot). As memories of the same component become organized around a com- mon frame, they implement a simulator that produces limitless simulations of the component (e.g., simulations of purr). Not only do such simulators develop for aspects of sensory experience, they also develop for aspects of proprioception (e.g., lift, run) and introspec- tion (e.g., compare, memory, happy, hungry). Once established, these simulators implement a basic conceptual system that represents types, supports categorization, and produces categorical inferences. These simulators further support productivity, propositions, and ab- stract concepts, thereby implementing a fully functional conceptual system. Productivity results from integrating simulators combinato- rially and recursively to produce complex simulations. Propositions result from binding simulators to perceived individuals to represent type-token relations. Abstract concepts are grounded in complex simulations of combined physical and introspective events. Thus, a per- ceptual theory of knowledge can implement a fully functional conceptual system while avoiding problems associated with amodal sym- bol systems. Implications for cognition, neuroscience, evolution, development, and artificial intelligence are explored. (shrink)

A cognitive ethnography of how bioengineering scientists create innovative modeling methods. In this first full-scale, long-term cognitive ethnography by a philosopher of science, Nancy J. Nersessian offers an account of how scientists at the interdisciplinary frontiers of bioengineering create novel problem-solving methods. Bioengineering scientists model complex dynamical biological systems using concepts, methods, materials, and other resources drawn primarily from engineering. They aim to understand these systems sufficiently to control or intervene in them. What Nersessian examines here is how cutting-edge bioengineering (...) scientists integrate the cognitive, social, material, and cultural dimensions of practice. Her findings and conclusions have broad implications for researchers in philosophy, science studies, cognitive science, and interdisciplinary studies, as well as scientists, educators, policy makers, and funding agencies. In studying the epistemic practices of scientists, Nersessian pushes the boundaries of the philosophy of science and cognitive science into areas not ventured before. She recounts a decades-long, wide-ranging, and richly detailed investigation of the innovative interdisciplinary modeling practices of bioengineering researchers in four university laboratories. She argues and demonstrates that the methods of cognitive ethnography and qualitative data analysis, placed in the framework of distributed cognition, provide the tools for a philosophical analysis of how scientific discoveries arise from complex systems in which the cognitive, social, material, and cultural dimensions of problem-solving are integrated into the epistemic practices of scientists. Specifically, she looks at how interdisciplinary environments shape problem-solving. Although Nersessian’s case material is drawn from the bioengineering sciences, her analytic framework and methodological approach are directly applicable to scientific research in a broader, more general sense, as well. (shrink)

One challenge while learning scientific concepts is to select relevant information and to integrate different representations of the learning content into one coherent mental model. Virtual reality learning environments offer new possibilities to support learners and foster learning processes. Whether learning in VR is successful, however, depends to a large extent on the design of the VRLE and the learners themselves. Hence, adding supportive elements in VRLEs, such as annotations, might facilitate the learning process by guiding attention and supporting the (...) selection of relevant information. Additionally, the mapping of pictorial and verbal information is eased by these annotations. The beneficial effect of annotations is highly dependent on learners' intrinsic motivation as intrinsic motivation while learning also affects the information selection and visual search patterns. In our experimental study, we compared two conditions: learning in a VRLE with or without annotations. We measured the learning outcome on three different levels. Additionally, we investigated intrinsic motivation as a moderator for the effect of annotations on learning outcome. We found no significant main effect of annotations on learning outcome. The moderating effect of intrinsic motivation for annotations on the overall learning outcome was significant. Our results imply that learners are either intrinsically motivated or need additional support by annotations as these support the selection of relevant information in the VRLE and therefore enable them to learn successfully. Which type or quantity of annotations supports learning processes best needs to be explored in future research. (shrink)

We are reminded of relevant stories, tales, or symbols from long-term memory when facing a novel problem our daily lives. Visual cues are 1 tool known to facilitate reminding. In 2 experiments, Chinese students, who had experienced a folk tale many years ago during childhood, were asked to solve an analogous problem. We tested the hypothesis that a visual cue can help bridge the gap between a novel problem and a source analogy experienced in the distant past. Different types of (...) cues proved to have distinct influences on components of analogical problem solving. This research suggests that analogical representational features of a story or problem can be stored in long-term memory and can be activated by visual cues. The implications of these findings for theories that point to perceptual or grounded, rather than decontextualized structures in knowledge representation are discussed. (shrink)

In some domains experts perform better than novices, and in other domains experts do not generally perform better than novices. According to empirical studies of expert performance, this is because the former but not the latter domains make available to training practitioners a direct form of learning feedback. Several philosophers resource this empirical literature to cast doubt on the quality of philosophical expertise. They claim that philosophy is like the dubious domains in that it does not make available the good, (...) direct kind of learning feedback, and thus there are empirical grounds for doubting the epistemic quality of philosophical expertise. I examine the empirical studies that are purportedly bad news for professional philosophers. On the basis of that examination, I provide three reasons why the empirical study of non-philosophical expertise does not undermine the status of philosophical expertise. First, the non-philosophical task-types from which the critics generalize are unrepresentative of relevant philosophical task-types. Second, empirical critiques of non-philosophical experts are often made relative to the performance of linear models—a comparison that is inapt in a philosophical context. Third, the critics fail to discuss findings from the empirical study of non-philosophical expertise that have more favorable implications for the epistemic status of philosophical expertise. In addition to discussing implications for philosophical expertise, this article makes progress in the philosophical analysis of the science of expertise and expert development. (shrink)

The use of analogy is an important component of human cognition. The type of analogy we produce and communicate depends heavily on a number of factors, such as the setting, the level of domain expertise present, and the speaker's goal or intent. In this observational study, we recorded economics experts during scientific discussion and examined the categorical distance and structural depth of the analogies they produced. We also sought to characterize the purpose of the analogies that were generated. Our results (...) supported previous conclusions about the infrequency of superficial similarity in subject-generated analogs, but also showed that distance and depth characteristics were more evenly balanced than in previous observational studies. This finding was likely due to the nature of the goals of the participants, as well as the broader nature of their expertise. An analysis of analogical purpose indicated that the generation of concrete source examples of more general target concepts was most prevalent. We also noted frequent instances of analogies intended to form visual images of source concepts. Other common purposes for analogies were the addition of colorful speech, inclusion (i.e., subsumption) of a target into a source concept, or differentiation between source and target concepts. We found no association between depth and either of the other _two_ characteristics, but our findings suggest a relationship between purpose and distance; i.e., that visual imagery typically entailed an outside-domain source whereas exemplification was most frequently accomplished using within-domain analogies. Overall, we observed a rich and diverse set of spontaneously produced analogical comparisons. The high degree of expertise within the observed group along with the richly comparative nature of the economics discipline likely contributed to this analogical abundance. (shrink)

Although case-based training is popular for ethics education, little is known about how specific case content influences training effectiveness. Therefore, the effects of (a) codes of ethical conduct and (b) forecasting content were investigated. Results revealed richer cases, including both codes and forecasting content, led to increased knowledge acquisition, greater sensemaking strategy use, and better decision ethicality. With richer cases, a specific pattern emerged. Specifically, content describing codes alone was more effective when combined with short-term forecasts, whereas content embedding codes (...) within context was more effective when combined with long-term forecasts, leading to greater knowledge acquisition and sensemaking strategy use. (shrink)

Detecting that two images are different is faster for highly dissimilar images than for highly similar images. Paradoxically, we showed that the reverse occurs when people are asked to describe how two images differ—that is, to state a difference between two images. Following structure-mapping theory, we propose that this disassociation arises from the multistage nature of the comparison process. Detecting that two images are different can be done in the initial (local-matching) stage, but only for pairs with low overlap; thus, (...) “different” responses are faster for low-similarity than for high-similarity pairs. In contrast, identifying a specific difference generally requires a full structural alignment of the two images, and this alignment process is faster for high-similarity pairs. We described four experiments that demonstrate this dissociation and show that the results can be simulated using the Structure-Mapping Engine. These results pose a significant challenge for nonstructural accounts of similarity comparison and suggest that structural alignment processes play a significant role in visual comparison. (shrink)

This study was aimed at explaining how and under what conditions surface similarity leads to the retrieval of an analogous base problem in LTM. Some elements of a theory of the organisation of knowledge in memory are proposed. Two levels of representation are distinguished. The first level represents directly accessible, local surface properties. The second level represents more abstract information pertaining to the category with which each analogous problem can be associated. Some results will be described showing that access to (...) an analogue in LTM based on surface properties is determined by the existence of a similarity at a higher level of abstraction. This is a search-area effect, in that categorical information seems to delimit a memory search space, within which the connection between local surface properties is more likely to be made. (shrink)

Analogical reasoning is often employed in problem-solving and metaphor interpretation. This paper submits that, as a default, analogical reasoning addressing these different tasks employs different mapping strategies: In problem-solving, it employs analogy-maximising strategies (like structure mapping, Gentner & Markman 1997); in metaphor interpretation, analogy-minimising strategies (like ATT-Meta, Barnden 2015). The two strategies interact in analogical reasoning with conceptual metaphors. This interaction leads to predictable fallacies. The paper supports these hypotheses through case-studies on ‘mind’-metaphors from ordinary discourse, and abstract problem-solving in (...) the philosophy of mind, respectively: It shows that (1) default metaphorical interpretations for vision- and space-cognition metaphors can be derived with a variant of the analogy-minimising ATT-Meta approach, (2) philosophically influential introspective conceptions of the mind can be derived with conceptual metaphors only through an analogy-maximising strategy, and (3) the interaction of these strategies leads to hitherto unrecognised fallacies in analogical reasoning with metaphors. This yields a debunking explanation of introspective conceptions. (shrink)

Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...) psychology. Despite the ubiquity of causal reasoning, textbooks of cognitive psychology have neglected this growing field. The goal of The Oxford Handbook of Causal Reasoning is to fill this gap. The handbook brings together the leading researchers in the field of causal reasoning and offers state-of-the-art presentations of theories and research. It provides introductions of competing theories of causal reasoning, and discusses its role in various cognitive functions and domains. The final section presents research from neighboring fields. 1. Causal Reasoning: An Introduction Michael R. Waldmann Part I: Theories of Causal Cognition 2. Associative Accounts of Causal Cognition Mike E. Le Pelley, Oren Griffiths, and Tom Beesley 3. Rules of Causal Judgment: Mapping Statistical Information Onto Causal Beliefs José C. Perales, Andrés Catena, Antonio Cándido, and Antonio Maldonado 4. The Inferential Reasoning Theory of Causal Learning: Toward a Multi- Process Propositional Account Yannick Boddez, Jan De Houwer, and Tom Beckers 5. Causal Invariance as an Essential Constraint for Creating a Causal Representation of the World: Generalizing the Invariance of Causal Power Patricia W. Cheng and Hongjing Lu 6. The Acquisition and Use of Causal Structure Knowledge Benjamin Margolin Rottman 7. Formalizing Prior Knowledge in Causal Induction Thomas L. Griffiths 8. Causal Mechanisms Samuel G. B. Johnson and Woo-kyoung Ahn 9. Force Dynamics and Causation Phillip Wolff and Robert Thorstad 10. Mental Models and Causation P. N. Johnson- Laird and Sangeet S. Khemlani 11. Pseudocontingencies Klaus Fiedler and Florian Kutzner 12. Singular Causation David Danks 13. Cognitive Neuroscience of Causal Reasoning Joachim T. Operskalski and Aron K. Barbey Part II: Basic Cognitive Functions 14. Visual Impressions of Causality Peter White 15. Goal-Directed Actions Bernhard Hommel 16. Planning and Control Magda Osman 17. Reinforcement Learning and Causal Models Samuel J. Gershman 18. Causation and the Probability of Causal Conditionals David E. Over 19. Causal Models and Conditional Reasoning Mike Oaksford and Nick Chater 20. Concepts as Causal Models: Categorization Bob Rehder 21. Concepts as Causal Models: Induction Bob Rehder 22. Causal Explanation Tania Lombrozo and Nadya Vasilyeva 23. Diagnostic Reasoning Björn Meder and Ralf Mayrhofer 24. Inferring Causal Relations by Analogy Keith J. Holyoak and Hee-Seung Lee 25. Causal Argument Ulrike Hahn, Roland Bluhm, and Frank Zenker 26. Causality in Decision- Making York Hagmayer and Philip M. Fernbach Part III: Domains of Causal Reasoning 27. Intuitive Theories Tobias Gerstenberg and Joshua B. Tenenbaum 28. Space, Time, and Causality Marc J. Buehner 29. Causation in Legal and Moral Reasoning David A. Lagnado and Tobias Gerstenberg 30. The Role of Causal Knowledge in Reasoning About Mental Disorders Woo-kyoung Ahn, Nancy S. Kim, and Matthew S. Lebowitz 31. Causality and Causal Reasoning in Natural Language Torgrim Solstad and Oliver Bott 32. Social Attribution and Explanation Denis Hilton Part IV: Development, Phylogeny, and Culture 33. The Development of Causal Reasoning Paul Muentener and Elizabeth Bonawitz 34. Causal Reasoning in Non-Human Animals Christian Schloegl and Julia Fischer 35. Causal Cognition and Culture Andrea Bender, Sieghard Beller, and Douglas L. Medin. (shrink)

Two experiments investigated whether infants represent goal‐directed actions of others in a way that allows them to draw inferences to unobserved states of affairs (such as unseen goal states or occluded obstacles). We measured looking times to assess violation of infants' expectations upon perceiving either a change in the actions of computer‐animated figures or in the context of such actions. The first experiment tested whether infants would attribute a goal to an action that they had not seen completed. The second (...) experiment tested whether infants would infer from an observed action the presence of an occluded object that functions as an obstacle. The looking time patterns of 12‐month‐olds indicated that they were able to make both types of inferences, while 9‐month‐olds failed in both tasks. These results demonstrate that, by the end of the first year of life, infants use the principle of rational action not only for the interpretation and prediction of goal‐directed actions, but also for making productive inferences about unseen aspects of their context. We discuss the underlying mechanisms that may be involved in the developmental change from 9 to 12 months of age in the ability to infer hypothetical (unseen) states of affairs in teleological action representations. (shrink)

We present five experiments and simulation studies to establish late analogical abstraction as a new psychological phenomenon: Schema abstraction from analogical examples can revive otherwise inert knowledge. We find that comparing two analogous examples of negotiations at recall time promotes retrieving analogical matches stored in memory—a notoriously elusive effect. Another innovation in this research is that we show parallel effects for real‐life autobiographical memory (Experiments 1–3) and for a controlled memory set (Experiments 4 and 5). Simulation studies show that a (...) unified model based on schema abstraction can capture backward (retrieval) effects as well as forward (transfer) effects. (shrink)

Empirical studies indicate that analogy consists of two main processes: retrieval and mapping. While current theories and models of analogy have revealed much about the mainly structural constraints that govern the mapping process, the similarities that underpin the correspondences between individual representational elements and drive retrieval are understood in less detail. In existing models symbol similarities are externally defined but neither empirically grounded nor theoretically justified. This paper introduces a new model (EMMA: the environmental model of analogy) which relies on (...) co‐occurrence information provided by LSA (Latent Semantic Analysis; Landauer & Dumais, 1997) to ground the relations between the symbolic elements aligned in analogy. LSA calculates a contextual distribution for each word encountered in a corpus by counting the frequency with which it co‐occurs with other words. This information is used to define a model that locates each word encountered in a high‐dimensional space, with relations between elements in this space representing contextual similarities between words. A series of simulation experiments demonstrate that the environmental approach to semantics embodied in LSA can produce appropriate patterns of analogical retrieval, but that this semantic measure is not sufficient to model analogical mapping. The implications of these findings, both for theories of representation in analogy research and more general theories of semantics in cognition, are explored. (shrink)

Blanchette and Dunbar have claimed that when participants are allowed to draw on their own source analogs in the service of analogical argumentation, retrieval is less constrained by surface similarity than traditional experiments suggest. In two studies, we adapted this production paradigm to control for the potentially distorting effects of analogy fabrication and uneven availability of close and distant sources in memory. Experiment 1 assessed whether participants were reminded of central episodes from popular movies while generating analogies for superficially similar (...) versus superficially dissimilar target situations. In Experiment 2, we modified this procedure to assess the retrieval of autobiographic memories, more familiar to participants than fictional episodes. Both studies revealed a strong effect of surface similarity on the retrieval of participants' own sources, thus suggesting that the superficial bias typically observed in experimental studies—and simulated by most computational models—does not originate in a lack of ecological validity. (shrink)

We present a model of similarity‐based retrieval that attempts to capture three seemingly contradictory psychological phenomena: (a) structural commonalities are weighed more heavily than surface commonalities in similarity judgments for items in working memory; (b) in retrieval, superficial similarity is more important than structural similarity; and yet (c) purely structural (analogical) remindings e sometimes experienced. Our model, MAC/FAC, explains these phenomena in terms of a two‐stage process. The first stage uses a computationally cheap, non‐structural matcher to filter candidate long‐term memory (...) items. It uses content vectors, a redundant encoding of structured representations whose dot product estimates how well the corresponding structural representations will match. The second stage uses SME (structure‐mapping engine) to compute structural matches on the handful of items found by the first stage. We show the utility of the MAC/FAC model through a series of computational experiments: (a) We demonstrate that MAC/FAC can model patterns of access found in psychological data; (b) we argue via sensitivity analyses that these simulation results rely on the theory; and (c) we compare the performance of MAC/FAC with ARCS, an alternate model of similarity‐based retrieval, and demonstrate that MAC/FAC explains the data better than ARCS. Finally, we discuss limitations and possible extensions of the model, relationships with other recent retrieval models, and place MAC/FAC in the context of other recent work on the nature of similarity. (shrink)

A theory of conceptual development must specify the innate representational primitives, must characterize the ways in which the initial state differs from the adult state, and must characterize the processes through which one is transformed into the other. The Origin of Concepts (henceforth TOOC) defends three theses. With respect to the initial state, the innate stock of primitives is not limited to sensory, perceptual, or sensorimotor representations; rather, there are also innate conceptual representations. With respect to developmental change, conceptual development (...) consists of episodes of qualitative change, resulting in systems of representation that are more powerful than, and sometimes incommensurable with, those from which they are built. With respect to a learning mechanism that achieves conceptual discontinuity, I offer Quinian bootstrapping. TOOC concludes with a discussion of how an understanding of conceptual development constrains a theory of concepts. (shrink)

We argue that existing learning algorithms are often poorly equipped to solve problems involving a certain type of important and widespread regularity that we call “type-2 regularity.” The solution in these cases is to trade achieved representation against computational search. We investigate several ways in which such a trade-off may be pursued including simple incremental learning, modular connectionism, and the developmental hypothesis of “representational redescription.”.

: Psychological explanations of philosophical intuitions can help us assess their evidentiary value, and our warrant for accepting them. To explain and assess conceptual or classificatory intuitions about specific situations, some philosophers have suggested explanations which invoke heuristic rules proposed by cognitive psychologists. The present paper extends this approach of intuition assessment by heuristics-based explanation, in two ways: It motivates the proposal of a new heuristic, and shows that this metaphor heuristic helps explain important but neglected intuitions: general factual intuitions (...) which have been highly influential in the philosophies of mind and perception but neglected in on-going debates in the epistemology of philosophy. To do so, the paper integrates results from three philosophically pertinent but hitherto largely unconnected strands of psychological research: research on intuitive judgement, analogy and metaphor, and memory-based processing, respectively. The paper shows that the heuristics-based explanation thus obtained satisfies the key requirements cognitive psychologists impose on such explanations, that it can explain the philosophical intuitions targeted, and that this explanation supports normative assessment of the intuitions' evidentiary value: It reveals whether particular intuitions are due to proper exercise of cognitive competencies or constitute cognitive illusions. (shrink)

This book contains a selection of the papers presented at the Logic, Reasoning and Rationality 2010 conference in Ghent. The conference aimed at stimulating the use of formal frameworks to explicate concrete cases of human reasoning, and conversely, to challenge scholars in formal studies by presenting them with interesting new cases of actual reasoning. According to the members of the Wiener Kreis, there was a strong connection between logic, reasoning, and rationality and that human reasoning is rational in so far (...) as it is based on logic. Later, this belief came under attack and logic was deemed inadequate to explicate actual cases of human reasoning. Today, there is a growing interest in reconnecting logic, reasoning and rationality. A central motor for this change was the development of non-classical logics and non-classical formal frameworks. The book contains contributions in various non-classical formal frameworks, case studies that enhance our apprehension of concrete reasoning patterns, and studies of the philosophical implications for our understanding of the notions of rationality. (shrink)

In this paper, I will propose a classification of analogies based on their internal structure. Selecting the criteria used in that classification first requires discussing the minimal constitutive parts of any analogy. Accordingly, I will discuss the differences between analogy and similarity and between analogy and “synalogy,” and I will stress the importance of the analogy of operations and procedures. Finally, I will set forth a classification of the different types of analogies, which lends itself to a further understanding of (...) the differences between certain modulations of the general idea of analogy, such as archetypes, prototypes, models, simulations, parables, paradigms, canons, maps, thought experiments, myths, utopias, dystopias and fables. (shrink)

While extremes tend to capture attention, the ordinary is often most of the story. So it may be with the structure-mapping process. The structure-mapping process can account for such pinnacles of thinking as analogy and metaphor, which can lead to overlooking the mundane, incremental use of structure mapping. Consequently, the current discussion shifts focus to the value of close comparisons between literally similar items for the development of knowledge. The intent is to foster greater integration between process and content as (...) well as between individuals and collectives. The payoff is identifying some undue simplifications and some promising new directions. (shrink)

One widely-endorsed argument in the experimental philosophy literature maintains that intuitive judgments are unreliable because they are influenced by the order in which thought experiments prompting those judgments are presented. Here, we explicitly state this argument from ordering effects and show that any plausible understanding of the argument leads to an untenable conclusion. First, we show that the normative principle is ambiguous. On one reading of the principle, the empirical observation is well-supported, but the normative principle is false. On the (...) other reading, the empirical observation has only weak support, and the normative principle, if correct, would impugn the reliability of deliberative reasoning, testimony, memory, and perception, since judgments in all these areas are sensitive to ordering in the relevant sense. We then reflect on what goes wrong with the argument. (shrink)

The current paper examines whether knowledge of an ethical principle influences moral awareness and ethical decision making. Using hypothetical scenarios and a behavioral task, three experiments examine the effects of deepening people’s knowledge of ethical principles. In each study, an analogical encoding learning intervention led to greater knowledge of an ethical principle, which in turn resulted in a greater likelihood of moral awareness and making ethical decisions. These findings suggest that moral awareness is partly a matter of the depth of (...) individuals’ knowledge of ethical principles. The findings provide further reasons to link work on ethics with work on expertise and knowledge transfer as well as indicate new approaches to ethics training. (shrink)

Manipulation of physical models such as tangrams and tiles is a popular approach to teaching early mathematics concepts. This pedagogical approach is extended by new computational media, where mathematical entities such as equations and vectors can be virtually manipulated. The cognitive and neural mechanisms supporting such manipulation-based learning—particularly how actions generate new internal structures that support problem-solving—are not understood. We develop a model of the way manipulations generate internal traces embedding actions, and how these action-traces recombine during problem-solving. This model (...) is based on a study of two groups of sixth-grade students solving area problems. Before problem-solving, one group manipulated a tangram, the other group answered a descriptive test. Eye-movement trajectories during problem-solving were different between the groups. A second study showed that this difference required the tangram's geometrical structure, just manipulation was not enough. We propose a theoretical model accounting for these results, and discuss its implications. (shrink)

Some regularities enjoy only an attenuated existence in a body of training data. These are regularities whose statistical visibility depends on some systematic recoding of the data. The space of possible recodings is, however, infinitely large – it is the space of applicable Turing machines. As a result, mappings that pivot on such attenuated regularities cannot, in general, be found by brute-force search. The class of problems that present such mappings we call the class of “type-2 problems.” Type-1 problems, by (...) contrast, present tractable problems of search insofar as the relevant regularities can be found by sampling the input data as originally coded. Type-2 problems, we suggest, present neither rare nor pathological cases. They are rife in biologically realistic settings and in domains ranging from simple animat behaviors to language acquisition. Not only are such problems rife – they are standardly solved! This presents a puzzle. How, given the statistical intractability of these type-2 cases, does nature turn the trick? One answer, which we do not pursue, is to suppose that evolution gifts us with exactly the right set of recoding biases so as to reduce specific type-2 problems to type-1 mappings. Such a heavy-duty nativism is no doubt sometimes plausible. But we believe there are other, more general mechanisms also at work. Such mechanisms provide general strategies for managing problems of type-2 complexity. Several such mechanisms are investigated. At the heart of each is a fundamental ploy – namely, the maximal exploitation of states of representation already achieved by prior, simpler learning so as to reduce the amount of subsequent computational search. Such exploitation both characterizes and helps make unitary sense of a diverse range of mechanisms. These include simple incremental learning, modular connectionism, and the developmental hypothesis of “representational redescription”. In addition, the most distinctive features of human cognition – language and culture – may themselves be viewed as adaptations enabling this representation/computation trade-off to be pursued on an even grander scale. (shrink)

A central goal of cognitive science is to develop a general theory of transfer to explain how people use and apply their prior knowledge to solve new problems. Previous work has identified multiple mechanisms of transfer including (but not limited to) analogy, knowledge compilation, and constraint violation. The central hypothesis investigated in the current work is that the particular profile of transfer processes activated for a given situation depends on both (a) the type of knowledge to be transferred and how (...) it is represented, and (b) the processing demands of the transfer task. This hypothesis was investigated in two laboratory training studies. The results from Experiment 1 show that each mechanism predicts specific behavioural patterns of performance across a common set of transfer tasks. The results from Experiment 2 show that people can adaptively shift between transfer mechanisms depending on their prior knowledge and the characteristics of the task environment. A framework for the development of a general theory of transfer based on multiple mechanisms is proposed and implications of the theory are discussed for measuring and understanding knowledge transfer. (shrink)

Analogy and similarity are central phenomena in human cognition, involved in processes ranging from visual perception to conceptual change. To capture this centrality requires that a model of comparison must be able to integrate with other processes and handle the size and complexity of the representations required by the tasks being modeled. This paper describes extensions to Structure-Mapping Engine since its inception in 1986 that have increased its scope of operation. We first review the basic SME algorithm, describe psychological evidence (...) for SME as a process model, and summarize its role in simulating similarity-based retrieval and generalization. Then we describe five techniques now incorporated into the SME that have enabled it to tackle large-scale modeling tasks: Greedy merging rapidly constructs one or more best interpretations of a match in polynomial time: O); Incremental operation enables mappings to be extended as new information is retrieved or derived about the base or target, to model situations where information in a task is updated over time; Ubiquitous predicates model the varying degrees to which items may suggest alignment; Structural evaluation of analogical inferences models aspects of plausibility judgments; Match filters enable large-scale task models to communicate constraints to SME to influence the mapping process. We illustrate via examples from published studies how these enable it to capture a broader range of psychological phenomena than before. (shrink)

Analogy is an important cognitive process that has been researched extensively. Functional accounts of it typically involve at least four stages of processing ; however, these accounts take the way in which the base analogue is understood, along with its relational structure, for granted. The goal of this paper is to open up a discussion about how this process may occur. To this end, this paper describes two experiments that vary the level of relational complexity across exemplars. It was found (...) that relational recognition tasks benefit from increased complexity, while mapping tasks suffer from it. (shrink)