The use of analogy in human thinking is examined from the perspective of a multiconstraint theory, which postu-lates 3 basic types of constraints: similarity, structure, and purpose. The operation of these constraints is appar-ent in laboratory experiments on analogy and in natural-istic settings, including politics, psychotherapy, and sci-entific research. The multiconstraint theory has been im-plemented in detailed computational simulations of the analogical human mind. ~ ~ any parents know that young children take comfort in getting a kiss on an injury to "make it better. " Little Aaron, aged 24 months, would routinely come to his mother saying things like, "I bump my head. Kiss it. " But one morning, for the first time ever, the tables turned. While his mother was dressing

We summarize selected recent developments and promising directions for improving the quality of models of human performance in synthetic environments. The potential uses and goals for behavioral models in synthetic environments are first summarized. Within that context, we examine relevant, current work related to modeling more complete performance, for example, on cognitive modeling of emotion, advanced techniques for testing and building models of behavior, new cognitive architectures, and agent and Belief, Desires and Intentions (BDI) technology. The report also considers the usability of these systems as an important but neglected aspect of their performance. A list of projects with high payoff for modeling human performance in synthetic environments is noted.

A reconceptualization of stigma is presented that changes the emphasis from the devaluation of an individual's identity to the process by which individuals who satisfy certain criteria come to be excluded from various kinds of social interactions. The authors propose that phenomena currently placed under the general rubric of stigma involve a set of distinct psychological systems designed by natural selection to solve specific problems associated with sociality. In particular, the authors suggest that human beings possess cognitive adaptations designed to cause them to avoid poor social exchange partners, join cooperative groups (for purposes of between-group competition and exploitation), and avoid contact with those who are differentially likely to carry communicable pathogens. The evolutionary view contributes to the current conceptualization of stigma by providing an account of the ultimate function of Stigmatization and helping to explain its consensual nature.

The theory-based model of categorization posits that concepts are represented as theories rather than as feature lists. Thus, it is particularly interesting that the DSM-IV (American Psychiatric Association, 1994), establishes a set of atheoretical guidelines for diagnosis in the domain of mental disorders. Five experiments investigated how clinicians handle an atheoretical nosology. Clinical psychologists' causal theories for DSM-IV disorders and their responses on diagnostic and memory tasks were measured. Participants were more likely to diagnose a hypothetical patient with a disorder if that patient had causally central rather than causally peripheral symptoms according to their theory of the disorder. They also showed biased memory for the causally central symptoms. Clinicians are cognitively driven to form and apply theories despite decades of training and practice with the DSM's atheoretical guidelines. Clinical Psychologists' Theory-Based Representations of Mental Disorders Predict their Diagnostic Reasoning and Memory The theory-based view of categorization proposes that concepts are represented as theories or causal explanations. Murphy and Medin (1985) suggested that our nave theories about the world hold the features of a concept together in a cohesive package. For instance, a layperson's concept of anorexia not only contains the features "fear of becoming fat" and "refuses to maintain minimal body weight," but also the notion that the fear of becoming fat helps cause the refusal to maintain minimal body weight (Kim & Ahn, 2002). Indeed, a growing body of evidence supports the notion that the human mind constantly seeks out rules and explanations that make sense of incoming data concerning its surroundings, and forms concepts based on its theories about the ...

Abstract—Although projective techniques continue to be widely used in clinical and forensic settings, their scientific status remains highly controversial. In this monograph, we review the current state of the literature concerning the psychometric properties (norms, reliability, validity, incremental validity, treatment utility) of three major projective instruments: Rorschach Inkblot Test, Thematic Apperception Test (TAT), and human figure drawings. We conclude that there is empirical support for the validity of a small number of indexes derived from the Rorschach and TAT. However, the substantial majority of Rorschach and TAT indexes are not empirically supported. The validity evidence for human figure drawings is even more limited. With a few exceptions, projective indexes have not consistently demonstrated incremental validity above and beyond other psychometric data. In addition, we summarize

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How should tasks be allocated dynamically between people and intelligent machines? What are the initial issues? Previous work on static task allocation and work on human performance when multi-tasking and when interrupted provides suggestions on how to dynamically allocate tasks between humans and machines. We use these results to explore previous theories of task allocation. Some of these theories have direct suggestions for dynamic task allocation and some have indirect implications. We use both types to provide a list of suggestions for creating systems that do dynamic task allocation. The context we will be working with is a type of pilot’s associate that has a description of the pilot’s tasks and flight mission built within a cognitive architecture. The proposed associate has an additional component that can match the pilot’s performance to these tasks, predict the flight phase and pilot’s current tasks, and use this information to dynamically allocate these tasks between the pilot and the automation. These suggestions are to inform the design of a high-level intelligent controller.

Decision aids are becoming more popular and more accessible thanks to the internet and hand held computers. The question remains, however, if decision aids can be used beyond just aiding the human decision process. Can we use computers to make decisions without loosing out on some of the aspects of decision making that are important to us? The aspects that will be dealt with are; transparency, consistency, accuracy, improvement, adaptability, and speed. In this master thesis I will present what these aspects mean to decisions, and how different models of decision making compare to human decision making with regard to them. For instance; how transparent and accurate are humans in their decision making compared to linear models, designed to fit the available data? I will also give some examples of decision

Abstractions and metaphors seem necessary for human and software agents to operate on the Internet. We hear about (virtual) desktops, classrooms, universities, sales rooms, shopping baskets, etc. We investigate this from a logical point of view emphasizing the syntax/semantics distinction and the use of abstractions to handle logical and computational complexity.

Recent scholars have dismissed the utility of self-esteem as well as programs designed to improve it. The authors challenge these contentions on conceptual, methodological, and empirical grounds. They begin by proposing that the scope of recent analyses has been overly narrow and should be broadened to include specific as well as global self-views. Using this conceptualization, the authors place recent critiques in historical context, recalling that similarly skeptical commentaries on global attitudes and traits inspired theorizing and empirical research that subsequently restored faith in the value of both constructs. Specifically, they point to 3 strategies for attaining more optimistic assessments of the predictive validity of selfviews: recognizing the utility of incorporating additional variables in predictive schemes, matching the specificity of predictors and criteria, and using theoretically informed standards for evaluating predictor–criterion relationships. The authors conclude that self-views do matter and that it is worthwhile and important to develop and implement theoretically informed programs to improve them.