Reasoning about make-believe and hypothetical suppositions: Towards a theory of belief-contravening reasoning

The present study explores how suppositions which conflict with accepted beliefs are represented and reasoned about. Two studies test the predictions regarding the nature and developmental changes in children's ability to represent and reason about hypothetical or make-believe suppositions which violate their everyday knowledge and beliefs. In Study 1, 46 4th- and 5th-graders were introduced to a hand puppet, Freddy, who made claims inconsistent with generally accepted beliefs (e.g., “all dogs meow”) because he was pretending (Make-Believe Condition) or believed them (Hypothetical Condition). Participants were asked to think like Freddy and judge whether a conclusion (“There's a dog; does it meow?”) follows logically from the claim. In Study 2, 40 kindergarten (6-year-olds), 3rd–4th grade (10-year-olds), and college students were asked to represent belief contravening make-believe (pretend in a make-believe world that dogs meow) and hypothetical (imagine what the real world would be like if dogs meow) premises, evaluate conclusions of the premises (Rover is a dog, does Rover meow?) and make judgments about the attributes (growl, wag tail, purr, and eat mice) of the entity (a meowing dog) they created. The prediction that it would be easier to represent and reason from belief-contravening suppositions in the Make-Believe than Hypothetical conditions was confirmed in each study, although the two forms of reasoning were directly correlated (Study 2). The results were discussed in terms of the similarities (compartmentalization and integration) and differences (reconciliation) of processes involved in fancifully (make-believe) or seriously (hypothetical) representing and reasoning about belief-contravening suppositions.     

Experience-grounded semantics: a theory for intelligent systems

An experience-grounded semantics is introduced for an intelligent reasoning system, which is adaptive, and works with insufficient knowledge and resources. According to this semantics, truth and meaning are defined with respect to the experience of the system – the truth value of a statement indicates the amount of available evidence, and the meaning of a term indicates its experienced relations with other terms. The major difference between experience-grounded semantics and model-theoretic semantics is that the former does not assume the sufficiency of knowledge and resources. This approach provides new ideas to the solution of some important problems in cognitive science.     

De‐escalation after repeated negative feedback: emergent expectations of failure

Research on willingness to make marginal investments (e.g., the escalation and sunk cost literatures) has often focused on project completion decisions, such as the “radar‐blank plane.” This paper discusses a fundamentally different type of marginal investment decision, that of couples deciding whether to continue infertility treatment in the face of repeated failures. Two experiments based on this context show that when people face multiple independent chances to achieve a valued goal but are unsure about chances of success, premature quitting or “de‐escalation” is the norm. Repeated negative feedback appears to induce individuals to see each successive failure as more and more diagnostic. As a result, even a short series of failed attempts evokes beliefs that future attempts will also fail. These emergent expectations of failure, generated by causal attribution processes, associative learning, and/or discounting of ambiguous information, appear very compelling and induce people to forgo profitable marginal investments. Copyright © 2004 John Wiley & Sons, Ltd.     

Reasoning through doing. Epistemic mediators in scientific discovery

The recent epistemological and cognitive studies concentrate on the concept of abduction, as a means to originate and refine new ideas. Traditional cognitive science and computational accounts concerning abduction aim at illustration discovery and creativity processes in terms of theoretical and “internal” aspects, by means of computational simulations and/or abstract cognitive models. I will illustrate in this paper that some typical internal abductive processes are involved in scientific reasoning and discovery (for example through radical innovations). Nevertheless, especially concrete manipulations of the external world constitute a fundamental passage in science: by a process of manipulative abduction it is possible to build prostheses (epistemic mediators) for human minds, by interacting with external objects and representations in a constructive way. In this manner it is possible to create implicit knowledge through doing and to produce various opportunity to find, for example, anomalies and fruitful new risky perspectives. This kind of embodied and unexpressed knowledge holds a key role in the subsequent processes of scientific comprehension and discovery.     

Abductive inference in defeasible reasoning: a model for research programmes

Abduction is regarded as the inference process that goes from observations to explanations within a more general context or theoretical framework. There are good characterizations of abduction of surprising observations in monotonic theories. Also, in normal logic programs there are a tight relation among SLDNF and the abduction of negative literals. However, a problem that faces abduction is the explanation of anomalous observations, i.e., observations that are contradictory with respect to the current theory. For this reason, in this work we will consider the problem of embedding abduction of surprising and anomalous observations in defeasible (nonmonotonic) theories. We discuss some issues arising the pragmatic acceptance of abductive inferences in defeasible theories, and how to accommodate anomalous observations and characterize all the possible outcomes that a defeasible theory may face when confronted with new evidence. We explore the use of partial structures approach as a semantic foundation for our system. Finally, we discuss an application of our system as a formal device for representing the methodology of scientific research programmes. In this representation, a programme is regarded as a defeasible theory that draws predictions. When confronted with surprising or anomalous observations, the programme protects itself by means of heuristic procedures, which are represented in our system as abductive inference procedures.     

Epistemology and artificial intelligence

In this essay we advance the view that analytical epistemology and artificial intelligence are complementary disciplines. Both fields study epistemic relations, but whereas artificial intelligence approaches this subject from the perspective of understanding formal and computational properties of frameworks purporting to model some epistemic relation or other, traditional epistemology approaches the subject from the perspective of understanding the properties of epistemic relations in terms of their conceptual properties. We argue that these two practices should not be conducted in isolation. We illustrate this point by discussing how to represent a class of inference forms found in standard inferential statistics. This class of inference forms is interesting because its members share two properties that are common to epistemic relations, namely defeasibility and paraconsistency. Our modeling of standard inferential statistical arguments exploits results from both logical artificial intelligence and analytical epistemology. We remark how our approach to this modeling problem may be generalized to an interdisciplinary approach to the study of epistemic relations.     

Reasoning serves argumentation in children

The argumentative theory of reasoning (Mercier & Sperber, in press-c) claims that reasoning evolved for argumentation: to find and evaluate arguments in dialogic contexts. The theory has drawn most of its supportive evidence from work with adults, leaving open the possibility that argumentive features of reasoning are in fact entirely learned. Evidence is reviewed here suggesting that the special relation between reasoning and argumentation holds at all ages. More specifically, it is argued that (a) children possess at least rudimentary argument skills, (b) they are able to reap the benefits of social reasoning from very early on, (c) confirmation bias is present as soon as they start to argue, and (d) children can be victims of the same biases that affect adults when they use reasoning in the wrong contexts. These claims strengthen the argumentative theory of reasoning and support a call for more research on the interactive features of reasoning in both adults and children.     

Probabilistic reasoning in prediction and diagnosis: Effects of problem type,response mode,and individual differences

In prediction, subset relations require that the probability of conjoined events is never higher than that of constituent events. However, people's judgments regularly violate this principle, producing conjunction errors. In diagnosis, the probability of a hypothesis normatively is often higher for conjoined cues. An online survey used a within‐subjects design to explore the degree to which participants (n = 347) differentiated diagnosis and prediction using matched scenarios and both choice and estimation responses. Conjunctions were judged more probable than a constituent in diagnosis (76%) more often than prediction (64%) and in choice (84%) more often than direct estimation (57%), with no interaction of type of task and response mode. Correlation, regression, and path analyses were used to determine the relationships among individual difference variables and the diagnosis and prediction tasks. Among the correlation findings was that time spent on the task predicted higher conjunction probabilities in diagnosis but not prediction and that class inclusion errors predicted increased conjunction errors in choice but not estimation. Need for cognition and numeracy were only minimally related to reasoning about conjunctions. Results are consistent with the idea that people may misapply diagnostic reasoning to the prediction task and consequently commit the conjunction error. Copyright © 2010 John Wiley & Sons, Ltd.     

Moral development, executive functioning, peak experiences and brain patterns in professional and amateur classical musicians: interpreted in light of a Unified Theory of Performance

This study compared professional and amateur classical musicians matched for age, gender, and education on reaction times during the Stroop color-word test, brainwaves during an auditory ERP task and during paired reaction-time tasks, responses on the Gibbs Sociomoral Reflection questionnaire, and self-reported frequencies of peak experiences. Professional musicians were characterized by: (1) lower color-word interference effects (Stroop task), (2) faster categorization of rare expected stimuli (P3b), and a trend for faster processing of rare unexpected stimuli (P3a), (3) higher scores on the Sociomoral Reflection questionnaire, and (4) more frequent peak experiences during rest, tasks, and sleep. Both groups had high values on the Brain Integration Scale. These findings are interpreted in light of a Unified Theory of Performance, which posits that effectiveness in any area is influenced by one’s level of mind-brain development—emotional, cognitive, moral, ego and cortical development—with higher mind-brain development supporting greater effectiveness in any domain.     

An analytic tableau calculus for a temporalised belief logic

A tableau is a refutation-based decision procedure for a related logic, and is among the most popular proof procedures for modal logics. In this paper, we present a labelled tableau calculus for a temporalised belief logic called TML⁺, which is obtained by adding a linear-time temporal logic onto a belief logic by the temporalisation method of Finger and Gabbay. We first establish the soundness and the completeness of the labelled tableau calculus based on the soundness and completeness results of its constituent logics. We then sketch a resolution-type proof procedure that complements the tableau calculus and also propose a model checking algorithm for TML⁺ based on the recent results for model checking procedures for temporalised logics. TML⁺ is suitable for formalising trust and agent beliefs and reasoning about their evolution for agent-based systems. Based on the logic TML⁺, the proposed labelled tableau calculus could be used for analysis, design and verification of agent-based systems operating in dynamic environments.