The authors present a theory of how relational inference and generalization can be accomplished within a cognitive architecture that is psychologically and neurally realistic. Their proposal is a form of symbolic connectionism: a connectionist system based on distributed representations of concept meanings, using temporal synchrony to bind fillers and roles into relational structures. The authors present a specific instantiation of their theory in the form of a computer simulation model, Learning and Inference with Schemas and Analogies (LISA). By using a kind of self-supervised learning, LISA can make specific inferences and form new relational generalizations and can hence acquire new schemas by induction from examples. The authors demonstrate the sufficiency of the model by using it to simulate a body of empirical phenomena concerning analogical inference and relational generalization. A fundamental aspect of human intelligence is the ability to form and manipulate relational representations. Examples of relational thinking include the ability to appreciate analogies between seemingly different objects or events (Gentner, 1983; Holyoak & Thagard, 1995), the ability to apply abstract rules in novel situations (e.g., Smith, Langston, & Nisbett, 1992), the ability to understand and learn language (e.g., Kim, Pinker, Prince, & Prasada, 1991), and even the ability to appreciate perceptual similarities

This paper reports and extends discussions carried out during a workshop held at the Santa Fe Institute in August 1995 by the authors. It treats eight major topics: (i) the importance of carefully examining research on routine, (it) the concept of 'action patterns ' in general and in terms of routine, (Hi) the useful categorization of routines and other recurring patterns, (iv) the research implications of recent cognitive results, (v) the relation of evolution to action patterns, (vi) the contributions of simulation modeling for theory in this area, (vii) examples of various approaches to empirical jj; research that reveal key problems, and (viii) a possible definition of 'routine'. An m extended appendix by Massimo Egidi provides a lexicon of synonyms and opposites ji covering use of the word 'routine ' in such areas as economics, organization theory and z artificial intelligence. 6

A developmental trajectory describes the course of a behavior over age or time. A group-based method for identifying distinctive groups of individual trajectories within the population and for profiling the characteristics of group members is demonstrated. Such clusters might include groups of "increasers. " "decreasers," and "no changers. " Suitably defined probability distributions are used to handle 3 data types—count, binary, and psychometric scale data. Four capabilities are demonstrated: (a) the capability to identify rather than assume distinctive groups of trajectories, (b) the capability to estimate the proportion of the population following each such trajectory group, (c) the capability to relate group membership probability to individual characteristics and circumstances, and (d) the capability to use the group membership probabilities for various other purposes such as creating profiles of group members. Over the past decade, major advances have been made in methodology for analyzing individual-level developmental trajectories. The two main branches of methodology are hierarchical modeling (Bryk &

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Although commentators periodically declare that Freud is dead, his repeated burials lie on shaky grounds. Critics typically attack an archaic version of psychodynamic theory that most clinicians similarly consider obsolete. Central to contemporary psychodynamic theory is a series of propositions about (a) unconscious cognitive, affective, and motivational processes; (b) ambivalence and the tendency for affective and motivational dynamics to operate in parallel and produce compromise solutions; (c) the origins of many personality and social dispositions in childhood; (d) mental representations of the self, others, and relationships; and (e) developmental dynamics. An enormous body of research in cognitive, social, developmental, and personality psychology now supports many of these propositions. Freud's scientific legacy has implications for a wide range of domains in psychology, such as integration of affective and motivational constraints into connectionist models in cognitive science. Freud, like Elvis, has been dead for a number of years but continues to be cited with some regularity. Although the majority of clinicians report that they rely to some degree upon psychodynamic 1 principles

Moddeling human conditional reasoning of the type "if p then q" containing negations poses a challenge for connectionism. A network of spiking neurons (INFERNET) was used to model this type of conditional reasoning. This model also provides insights on certain human limitations. The model is compared to empirical data, and classical explanations. Statistical analysis shows that the model's performance not only surpasses classical explanations but also provides a very good overall fit to empirical data. INFERNET simulator results are also compared to human performance. The simulations compare well with both human performance and limitations. Introduction INFERNET (Sougn, 1996, 1998a, 1998b, Sougn & French, 1997) achieves variable binding through temporal synchrony of node firing. In short, when one node fires in synchrony with another, they are temporarily bound together. It has a limited Working Memory (WM) span and the content of WM is maintained by oscillations. Once a ...

The recognition heuristic (RH; Goldstein & Gigerenzer, 2002) suggests that, when applicable, probabilistic inferences are based on a noncompensatory examination of whether an object is recognized or not. The overall findings on the processes that underlie this fast and frugal heuristic are somewhat mixed, and many studies have expressed the need for considering a more compensatory integration of recognition information. Regardless of the mechanism involved, it is clear that recognition has a strong influence on choices, and this finding might be explained by the fact that recognition cues arouse affect and thus receive more attention than cognitive cues. To test this assumption, we investigated whether recognition results in a direct affective signal by measuring physiological arousal (i.e., peripheral arterial tone) in the established city-size task. We found that recognition of cities does not directly result in increased physiological arousal. Moreover, the results show that physiological arousal increased with increasing inconsistency between recognition information and additional cue information. These findings support predictions derived by a compensatory Parallel Constraint Satisfaction model rather than predictions of noncompensatory models. Additional results concerning confidence ratings, response times, and choice proportions further demonstrated that recognition information and other cognitive cues are integrated in a compensatory manner.

: Previous researchers have discovered perplexing inconsistencies in how human subjects appear to utilize knowledge of category base rates when making category judgments. In particular, Medin and Edelson (1988) found an "inverse base rate effect" in which subjects tended to select a rare category when tested with a combination of conflicting cues, and Gluck and Bower (1988) reported apparent "base rate neglect" in which subjects tended to select a rare category when tested with a single symptom whose objective diagnosticity was equal for all categories. In this article I suggest that two principles underlie those effects: First, base rate information is learned and consistently deployed during all training and testing cases. Second, the dominant effect of base rates is to cause frequent categories to be learned before rare categories, so that the common categories are encoded in terms of their typical features, and the rare categories are encoded by whichever features distinguish them ...

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*NB: This is a still incomplete version!** 1