Most theories of deduction have assumed that linguistic processes transduce from language into an internal representation and back again, and that non-linguistic processes are central to deduction itself. In this article it is proposed that for deduction tasks for which the necessary information is provided verbally, the heart of deduction for untrained participants involves repeatedly reencoding the problem, a type of behavior referred to here as verbal reasoning. It is shown that model theory accounts of behavior on most deduction tasks (...) are consistent with verbal reasoning and that verbal reasoning can account for detailed behavior in a single task; a computational model of syllogistic reasoning—VR—based on linguistic mechanisms is presented. VR models all of the standard phenomena, makes a number of accurate novel predictions, and fits the behavior of individual participants with an accuracy that rivals their own test–retest reliability. (shrink)

In some views of cognitive science, episodic memory is simply one of many pieces of the puzzle of cognition: MEMORY, REASONING, and learning can be studied largely independently of one another. The case‐based reasoning (CBR) stance takes the contrasting position that human reasoning, memory, and learning are inextricably bound together. In this view, reasoning is primarily based on remembering and reapplying the lessons of prior episodes. A case‐based problem‐solver, for example, solves new problems by retrieving traces of relevant prior problems (...) from memory, establishing correspondences between those problems and the new situation, and adapting the prior solutions to fit the problem at hand. Learning is a natural side effect of this process, as traces of new episodes are stored for future use. (shrink)

We resolve the two problems that Hardman raises. The first problem arises from a misunderstanding: the crucial distinction is between one-model and multiple-model problems. The second problem illuminates a deeper principle: conclusions depend on the procedures for interpreting models. We describe an algorithm that obviates the problem and empirical work that reveals a new view of syllogistic reasoning.

The mental model theory postulates that reasoners build models of the situations described in premises. A conclusion is possible if it holds in at least one model of the premises; it is probable if it holds in most of the models; and it is necessary if it holds in all of the models. The theory also postulates that reasoners represent as little information as possible in explicit models and, in particular, that they represent only information about what is true. One (...) unexpected consequence of this assumption is that there should be a category of illusory inferences: they will have conclusions that seem obvious, but that are wholly erroneous. Experiment 1 established the existence of such illusory inferences about probabilities. Overall, 88% of the intelligent adult subjects chose as more probable an outcome that was impossible for at least one of the illusory problems. Experiment 2 corroborated the phenomenon and showed that illusory inferences include a wide variety of problems. Finally, the paper argues that current theories based on formal rules of inference are unlikely to be able to explain the illusions. (shrink)

When reasoning about deontic rules (what one may, should, or should not do in a given set of circumstances), reasoners adopt a violation‐detection strategy, a strategy they do not adopt when reasoning about indicative rules (descriptions of purported state of affairs). I argue that this indicative‐deontic distinction constitutes a primitive in the cognitive architecture. To support this claim, I show that this distinction emerges early in development, is observed regardless of the cultural background of the reasoner, and can be selectively (...) disrupted at the neurological level. I also argue that this distinction emerged as a result of selective pressure favouring the evolution of reasoning strategies that determine survival within dominance hierarchies. (shrink)

We propose that people typically reason about realistic situations using neither content-free syntactic inference rules nor representations of specific experiences. Rather, people reason using knowledge structures that we term pragmatic reasoning schemas, which are generalized sets of rules defined in relation to classes of goals. Three experiments examined the impact of a “permission schema” on deductive reasoning. Experiment 1 demonstrated that by evoking the permission schema it is possible to facilitate performance in Wason's selection paradigm for subjects who have had (...) no experience with the specific content of the problems. Experiment 2 showed that a selection problem worded in terms of an abstract permission elicited better performance than one worded in terms of a concrete but arbitrary situation, providing evidence for an abstract permission schema that is free of domain-specific content. Experiment 3 provided evidence that evocation of a permission schema affects not only tasks requiring procedural knowledge, but also a linguistic rephrasing task requiring declarative knowledge. In particular, statements in the form if p then q were rephrased into the form p only if q with greater frequency for permission than for arbitrary statements, and rephrasings of permission statements produced a pattern of introduction of modals totally unlike that observed for arbitrary conditional statements. Other pragmatic schemas, such as “causal” and “evidence” schemas can account for both linguistic and reasoning phenomena that alternative hypotheses fail to explain. (shrink)

In this study on deduction, the authors argue that people reason by imagining the relevant state of affairs, ie building an internal model of it, formulating a tentative conclusion based on this model and then searching for alternative models.

Existing accounts of syllogistic reasoning oppose rule-based and model-based methods. Stenning \& Oberlander show that the latter are isomorphic to well-known graphical methods, when these are correctly interpreted. We here extend these results by showing that equivalent sentential implementations exist, thus revealing that all these theories are members of a family of abstract {\it individual identification algorithms} variously implemented in diagrams or sentences. This abstract logical analysis suggests a novel {\it individual identification task} for observing syllogistic reasoning processes. Comparison of (...) the results of this task with the Standard Task confirms that the tasks are psychologically closely related, throwing light on sources of error, on subjects' sensitivity to metalogical properties, and on term ordering phenomena. Since it avoids posing the sub-task of formulating a quantified conclusion, the new task allows comparison of explanations of problem difficulty in terms of the number of models with alternatives in terms of the difficulty of choosing a quantifier for the conclusion. Logical concepts of {\it source} and {\it conditional} premisses provide a comprehensive account of term order data, including figural effects, at a level abstract with regard to imagistic or sentential representations. These results argue that much richer empirical evidence will be required to discriminate phenomenologically distinct reasoning processes than has hitherto been supposed. (shrink)

The following values have no corresponding Zotero field: PB - Lawrence Erlbaum Associates Inc Mahwah, NJ.