This volume features the complete text of the material presented at the Twentieth Annual Conference of the Cognitive Science Society. As in previous years, the symposium included an interesting mixture of papers on many topics from researchers with diverse backgrounds and different goals, presenting a multifaceted view of cognitive science. This volume contains papers, posters, and summaries of symposia presented at the leading conference that brings cognitive scientists together to discuss issues of theoretical and applied concern. Submitted presentations are represented in these proceedings as "long papers" (those presented as spoken presentations and "full posters" at the conference) and "short papers" (those presented as "abstract posters" by members of the Cognitive Science Society).

The International Conference on Cognitive Modeling brings together researchers who develop computational models to explain and predict cognitive data. The core theme of the 2004 conference was "Integrating Computational Models," encompassing an integration of diverse data through models of coherent phenomena; integration across modeling approaches; and integration of teaching and modeling. This text presents the proceedings of that conference. The International Conference on Cognitive Modeling 2004 sought to grow the discipline of computational cognitive modeling by providing a sophisticated modeling audience for cutting-edge researchers, in addition to offering a forum for integrating insights across alternative modeling approaches in both basic research and applied settings, and a venue for planning the future growth of the discipline. The meeting included a careful peer-review process of 6-page paper submissions; poster-abstracts to include late-breaking work in the area; prizes for best papers; a doctoral consortium; and competitive modeling symposia that compare and contrast different approaches to the same phenomena.

The International Conference on Cognitive Modeling brings together researchers who develop computational models that explain and predict cognitive data. The 2004 conference encompassed an integration of diverse data through models of coherent phenomena;

The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. These proceedings contain all of the papers that were presented.

Studying narratives is often the best way to gain a good understanding of how various aspects of human information are organized and integrated—the narrator employs specific informational methods to build the whole structure of a narrative through combining temporally constructed events in light of an array of relationships to the narratee and these methods reveal the interaction of the rational and the sensitive aspects of human information. Computational and Cognitive Approaches to Narratology discusses issues of narrative-related information and communication technologies, cognitive mechanism and analyses, and theoretical perspectives on narratives and the story generation process. Focusing on emerging research as well as applications in a variety of fields including marketing, philosophy, psychology, art, and literature, this timely publication is an essential reference source for researchers, professionals, and graduate students in various information technology, cognitive studies, design, and creative fields.

The leading thinkers from the cognitive science tradition participated in a workshop sponsored by Sandia National Laboratories in July of 2003 to discuss progress in building their models. The goal was to summarize the theoretical and empirical bases for cognitive systems and to present exemplary developments in the field. Following the workshop, a great deal of planning went into the creation of this book. Eleven of the twenty-six presenters were asked to contribute chapters, and four chapters are the product of the breakout sessions in which critical topics were discussed among the participants. An introductory chapter provides the context for this compilation. Cognitive Systems thus presents a unique merger of cognitive modeling and intelligent systems, and attempts to overcome many of the problems inherent in current expert systems. It will be of interest to researchers and students in the fields of cognitive science, computational modeling, intelligent systems, artificial intelligence, and human-computer interaction.

The Oxford Handbook of Cognitive Science emphasizes the research and theory most central to modern cognitive science: computational theories of complex human cognition. Additional facets of cognitive science are discussed in the handbook's introductory chapter.

Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that the multi-objective approach to machine learning is particularly successful to improve the performance of the traditional single objective machine learning methods, to generate highly diverse multiple Pareto-optimal models for constructing ensembles models and, and to achieve a desired trade-off between accuracy and interpretability of neural networks or fuzzy systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems.