Current theories of reasoning such as mental models or mental logic assume a universal cognitive mechanism that underlies human reasoning performance. However, there is evidence that this is not the case, for example, the work of Ford (1995), who found that some people adopted predominantly spatial and some verbal strategies in a syllogistic reasoning task. Using written and think-aloud protocols, the present study confirmed the existence of these individual differences. However, in sharp contrast to Ford, the present study found few (...) differences in reasoning performance between the two groups, in terms of accuracy or type of conclusion generated. Hence, reasoners present an outward appearance of ubiquity, despite underlying differences in reasoning processes. These findings have implications for theoretical accounts of reasoning, and for attempts to model reasoning data. Any comprehensive account needs to account for strategic differences and how these may develop in logically untrained individuals. (shrink)

The article first addresses the importance of cognitive modeling, in terms of its value to cognitive science (as well as other social and behavioral sciences). In particular, it emphasizes the use of cognitive architectures in this undertaking. Based on this approach, the article addresses, in detail, the idea of a multi-level approach that ranges from social to neural levels. In physical sciences, a rigorous set of theories is a hierarchy of descriptions/explanations, in which causal relationships among entities at a high (...) level can be reduced to causal relationships among simpler entities at a more detailed level. We argue that a similar hierarchy makes possible an equally productive approach toward cognitive modeling. The levels of models that we conceive in relation to cognition include, at the highest level, sociological/anthropological models of collective human behavior, behavioral models of individual performance, cognitive models involving detailed mechanisms, representations, and processes, as well as biological/physiological models of neural circuits, brain regions, and other detailed biological processes. (shrink)

Interpretation is the process whereby a hearer reasons to an interpretation of a speaker's discourse. The hearer normally adopts a credulous attitude to the discourse, at least for the purposes of interpreting it. That is to say the hearer tries to accommodate the truth of all the speaker's utterances in deriving an intended model. We present a nonmonotonic logical model of this process which defines unique minimal preferred models and efficiently simulates a kind of closed-world reasoning of particular interest for (...) human cognition. Byrne's “suppression” data (Byrne, 1989) are used to illustrate how variants on this logic can capture and motivate subtly different interpretative stances which different subjects adopt, thus indicating where more fine-grained empirical data are required to understand what subjects are doing in this task. We then show that this logical competence model can be implemented in spreading activation network models. A one pass process interprets the textual input by constructing a network which then computes minimal preferred models for (3-valued) valuations of the set of propositions of the text. The neural implementation distinguishes easy forward reasoning from more complex backward reasoning in a way that may be useful in explaining directionality in human reasoning. (shrink)

Interpretation is the process whereby a hearer reasons to an interpretation of a speaker's discourse. The hearer normally adopts a credulous attitude to the discourse, at least for the purposes of interpreting it. That is to say the hearer tries to accommodate the truth of all the speaker's utterances in deriving an intended model. We present a nonmonotonic logical model of this process which defines unique minimal preferred models and efficiently simulates a kind of closed-world reasoning of particular interest for (...) human cognition. Byrne's “suppression” data (Byrne, 1989) are used to illustrate how variants on this logic can capture and motivate subtly different interpretative stances which different subjects adopt, thus indicating where more fine-grained empirical data are required to understand what subjects are doing in this task. We then show that this logical competence model can be implemented in spreading activation network models. A one pass process interprets the textual input by constructing a network which then computes minimal preferred models for (3-valued) valuations of the set of propositions of the text. The neural implementation distinguishes easy forward reasoning from more complex backward reasoning in a way that may be useful in explaining directionality in human reasoning. (shrink)

Much research in the last two decades has demonstrated that human responses deviate from the performance deemed normative according to various models of decision making and rational judgment (e.g., the basic axioms of utility theory). This gap between the normative and the descriptive can be interpreted as indicating systematic irrationalities in human cognition. However, four alternative interpretations preserve the assumption that human behavior and cognition is largely rational. These posit that the gap is due to (1) performance errors, (2) computational (...) limitations, (3) the wrong norm being applied by the experimenter, and (4) a different construal of the task by the subject. In the debates about the viability of these alternative explanations, attention has been focused too narrowly on the modal response. In a series of experiments involving most of the classic tasks in the heuristics and biases literature, we have examined the implications of individual differences in performance for each of the four explanations of the normative/descriptive gap. Performance errors are a minor factor in the gap; computational limitations underlie non-normative responding on several tasks, particularly those that involve some type of cognitive decontextualization. Unexpected patterns of covariance can suggest when the wrong norm is being applied to a task or when an alternative construal of the task should be considered appropriate. Key Words: biases; descriptive models; heuristics; individual differences; normative models; rationality; reasoning. (shrink)

Two notions from philosophical logic and linguistics are brought together and applied to the psychological study of defeasible conditional reasoning. The distinction between disabling conditions and alternative causes is shown to be a special case of Pollock’s (1987) distinction between ‘rebutting’ and ‘undercutting’ defeaters. ‘Inferential’ conditionals are shown to come in two varieties, one that is sensitive to rebutters, the other to undercutters. It is thus predicted and demonstrated in two experiments that the type of inferential conditional used as the (...) major premise of conditional arguments can reverse the heretofore classic, distinctive effects of defeaters. (shrink)

Two notions from philosophical logic and linguistics are brought together and applied to the psychological study of defeasible conditional reasoning. The distinction between disabling conditions and alternative causes is shown to be a special case of Pollock’s (1987) distinction between ‘rebutting’ and ‘undercutting’ defeaters. ‘Inferential’ conditionals are shown to come in two varieties, one that is sensitive to rebutters, the other to undercutters. It is thus predicted and demonstrated in two experiments that the type of inferential conditional used as the (...) major premise of conditional arguments can reverse the heretofore classic, distinctive effects of defeaters. (shrink)

In this paper, the theory of syllogistic reasoning proposed by Johnson-Laird is shown to be inadequate and an alternative theory is put forward. Protocols of people attempting to solve syllogistic problems and explaining to another person how they reached their conclusions were obtained. Two main groups of subjects were identified. One group represented the relationship between classes in a spatial manner that was supplemented by a verbal representation. The other group used a primarily verbal representation. A detailed theory of the (...) processes for both groups is given. (shrink)

In this paper, I show that the question of how dual process theories of reasoning and judgement account for conflict between System 1 (heuristic) and System 2 (analytic) processes needs to be explicated and addressed in future research work. I demonstrate that a simple additive probability model that describes such conflict can be mapped on to three different cognitive models. The pre-emptive conflict resolution model assumes that a decision is made at the outset as to whether a heuristic or analytic (...) process will control the response. The parallel-competitive model assumes that each system operates in parallel to deliver a putative response, resulting sometimes in conflict that then needs to be resolved. Finally, the default-interventionist model involves the cueing of default responses by the heuristic system that may or may not be altered by subsequent intervention of the analytic system. A second, independent issue also emerges from this discussion. The superior performance of higher-ability participants on reasoning tasks may be due to the fact that they engage in more analytic reasoning ( quantity hypothesis ) or alternatively to the fact that the analytic reasoning they apply is more effective ( quality hypothesis ). (shrink)

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)

Logical argument forms are investigated by second order probability density functions. When the premises are expressed by beta distributions, the conclusions usually are mixtures of beta distributions. If the shape parameters of the distributions are assumed to be additive (natural sampling), then the lower and upper bounds of the mixing distributions (P´olya-Eggenberger distributions) are parallel to the corresponding lower and upper probabilities in conditional probability logic.