This paper evaluates four competing psychological explanations for why the jury in the O.J. Simpson murder trial reached the verdict they did: explanatory coherence, Bayesian probability theory, wishful thinking, and emotional coherence. It describes computational models that provide detailed simulations of juror reasoning for explanatory coherence, Bayesian networks, and emotional coherence, and argues that the latter account provides the most plausible explanation of the jury's decision.

This paper uses a psychological/computational theory of emotional coherence to explain several aspects of religious belief and practice. After reviewing evidence for the importance of emotion to religious thought and cognition in general, it describes psychological and social mechanisms of emotional cognition. These mechanisms are relevant to explaining the acquisition and maintenance of religious belief, and also shed light on such practices as prayer and other rituals. These psychological explanations are contrasted with ones based on biological evolution.

The authors present a neurological theory of how cognitive information and emotional information are integrated in the nucleus accumbens during effective decision making. They describe how the nucleus accumbens acts as a gateway to integrate cognitive information from the ventromedial prefrontal cortex and the hippocampus with emotional information from the amygdala. The authors have modeled this integration by a network of spiking artificial neurons organized into separate areas and used this computational model to simulate 2 kinds of cognitive–affective integration. The (...) model simulates successful performance by people with normal cognitive–affective integration. The model also simulates the historical case of Phineas Gage as well as subsequent patients whose ability to make decisions became.. (shrink)

Choosing the right plan is often choosing the more coherent plan: but what is coherence? We argue that coherence-directed practical inference ought to be represented computationally. To that end, we advance a theory of deliberative coherence, and describe its implementation in a program modelled on Thagard's ECHO. We explain how the theory can be tested and extended, and consider its bearing on instrumentalist accounts of practical rationality.

The concept of mechanism is analyzed in terms of entities and activities, organized such that they are productive of regular changes. Examples show how mechanisms work in neurobiology and molecular biology. Thinking in terms of mechanisms provides a new framework for addressing many traditional philosophical issues: causality, laws, explanation, reduction, and scientific change.

We contend that empathy is best viewed as a kind of analogical thinking of the sort described in the multiconstraint theory of analogy proposed by Keith Holyoak and Paul Thagard (1995). Our account of empathy reveals the Theory-theory/Simulation theory debate to be based on a false assumption and formulated in terms too simple to capture the nature of mental state ascription. Empathy is always simulation, but may simultaneously include theory-application. By properly specifying the analogical processes of empathy and their constraints, (...) we are able to show how the amount of theory needed to empathize is determined. (shrink)

Linking the process of rational decision making to emotions, an award-winning scientist who has done extensive research with brain-damaged patients notes the dependence of thought processes on feelings and the body's survival-oriented regulators. 50,000 first printing.

Hutchins examines a set of phenomena that have fallen between the established disciplines of psychology and anthropology, bringing to light a new set of relationships between culture and cognition.

Despite the growing appreciation of the relevance of affect to cognition, analogy researchers have paid remarkably little attention to emotion. This paper discusses three general classes of analogy that involve emotions. The most straightforward are analogies and metaphors about emotions, for example "Love is a rose and you better not pick it." Much more interesting are analogies that involve the transfer of emotions, for example in empathy in which people understand the emotions of others by imagining their own emotional reactions (...) in similar situations. Finally, there are analogies that generate emotions, for example analogical jokes that generate emotions such as surprise and amusement. (shrink)

In their introduction to this volume, Ram and Leake usefully distinguish between task goals and learning goals. Task goals are desired results or states in an external world, while learning goals are desired mental states that a learner seeks to acquire as part of the accomplishment of task goals. We agree with the fundamental claim that learning is an active and strategic process that takes place in the context of tasks and goals (see also Holland, Holyoak, Nisbett, and Thagard, 1986). (...) But there are important questions about the nature of goals that have rarely been addressed. First, how can a cognitive system deal with incompatible task goals? Someone may want both to get lots of research done and to relax and have fun with his or her friends. Learning how to accomplish both these tasks will take place in the context of goals that cannot be fully realized together. Second, how are goals chosen in the first place and why are some goals judged to be more important than others? People do not simply come equipped with goals and priorities: we sometimes have to learn what is important to us by adjusting the importance of goals in the context of other compatible and incompatible goals. This paper presents a theory and a computational model of how goals can be adopted or rejected in the context of decision making. In contrast to classical decision theory, it views decision making as a process not only of choosing actions but also of evaluating goals. Our theory can therefore be construed as concerned with the goal-directed learning of goals. (shrink)