Markov decision processes have become the de facto standard in modeling and solving sequential decision making problems under uncertainty. This book studies lifting Markov decision processes, reinforcement learning and dynamic programming to the first-order (or, relational) setting.

THE book is not a treatise on aIl cerebral mechanisms but a pro poscd solution of a specific problem: the origin of the nervous system's unique ability to produce adaptive behaviour. The work has as basis the fact that the nervous system behaves adap tively and the hypothesis that it is essentiaIly mechanistic; it proceeds on the assumption that these two data are not irrecon cilable. It attempts to deduce from the observed facts what sort of a mechanism it must be that behaves so differently from any machinc made so far. Other proposed solutions have usuaIly left open the question whether so me different theory might not fit the facts equaIly weIl: I have attempted to deduce what is necessary, what properties the nervous system must have if it is to behave at once mechanisticaIly and adaptively. For the deduction to be rigorous, an adequately developed logic of mechanism is essential. Until recently, discussions of mechan ism were carried on almost entirely in terms of so me particular embodiment-the mechanical, the electronic, the neuronie, and so on. Those days are past. There now exists a weIl-developed logic of pure mechanism, rigorous as geometry, and likely to play the same fundamental part, in our understanding of the complex systems of biology, that geometry does in astronomy. Only by the dcvelopment of this basic logic has thc work in this book been made possible.

This handbook is the first comprehensive text on positive psychology and disability. Emphasizing paradigmatic changes in understanding disability, the text covers traditional disciplines in positive psychology; and applications of positive psychology to domains like education or work.

The present book is the product of conferences held in Bielefeld at the Center for interdisciplinary Sturlies (ZiF) in connection with a year-long ZiF Research Group with the theme "Prerational intelligence". The premise ex plored by the research group is that traditional notions of intelligent behav ior, which form the basis for much work in artificial intelligence and cog nitive science, presuppose many basic capabilities which are not trivial, as more recent work in robotics and neuroscience has shown, and that these capabilities may be best understood as ernerging from interaction and coop eration in systems of simple agents, elements that accept inputs from and act upon their surroundings. The main focus is on the way animals and artificial systems process in formation about their surroundings in order to move and act adaptively. The analysis of the collective properties of systems of interacting agents, how ever, is a problern that occurs repeatedly in many disciplines. Therefore, contributions from a wide variety of areas have been included in order to obtain a broad overview of phenomena that demoostrate complexity arising from simple interactions or can be described as adaptive behavior arising from the collective action of groups of agents. To this end we have invited contributions on topics ranging from the development of complex structures and functions in systems ranging from cellular automata, genetic codes, and neural connectivity to social behavior and evolution. Additional contribu tions discuss traditional concepts of intelligence and adaptive behavior. 1.

In this wide-ranging work, now available in paperback, Habermas presents his views on the nature of the social sciences and their distinctive methodology and concerns. He examines, among other things, the traditional division between the natural sciences and the social sciences; the characteristics of social action and the implications of theories of language for social enquiry; and the nature, tasks and limitations of hermeneutics. Habermas' analysis of these and other themes is, as always, rigorous, perceptive and constructive. This brilliant study succeeds in highlighting the distinctive characteristics of the social sciences and in outlining the nature of, and prospects for, critical theory today.

In everyday life, and particularly in the modern workplace, information technology and automation increasingly mediate, augment, and sometimes even interfere with how humans interact with their environment. How to understand and support cognition in human-technology interaction is both a practically and socially relevant problem. The chapters in this volume frame this problem in adaptive terms: How are behavior and cognition adapted, or perhaps ill-adapted, to the demands and opportunities of an environment where interaction is mediated by tools and technology? The authors draw heavily on the work of Egon Brunswik, a pioneer in ecological and cognitive psychology, as well as on modern refinements and extensions of Brunswikian ideas, including Hammond's Social Judgment Theory, Gigerenzer's Ecological Rationality and Anderson's Rational Analysis. Inspired by Brunswik's view of cognition as "coming to terms" with the "casual texture" of the external world, the chapters in this volume provide quantitative and computational models and measures for studying how people come to terms with an increasingly technological ecology, and provide insights for supporting cognition and performance through design, training, and other interventions. The methods, models, and measures presented in this book provide timely and important resources for addressing problems in the rapidly growing field of human-technology interaction. The book will be of interest to researchers, students, and practitioners in human factors, cognitive engineering, human-computer interaction, judgment and decision making, and cognitive science.

Scientific research is viewed as a deliberate activity and the logic of discovery consists of strategies and arguments whereby the best objectives (questions) and optimal means for achieving these objectives (heuristics) are chosen. This book includes a discussion and some proposals regarding the way the logic of questions can be applied to understanding scientific research and draws upon work in artificial intelligence in a discussion of heuristics and methods for appraising heuristics (metaheuristics). It also includes a discussion of a third source for scientific objectives and heuristics; episodes and examplars from the history of science and the history of philosophy. This book is written to be accessible to advanced students in philosophy and to the scientific community. It is of interest to philosophers of science, philosophers of biology, historians of physics, and historians of biology.

The first comprehensive treatment of active inference, an integrative perspective on brain, cognition, and behavior used across multiple disciplines. Active inference is a way of understanding sentient behavior—a theory that characterizes perception, planning, and action in terms of probabilistic inference. Developed by theoretical neuroscientist Karl Friston over years of groundbreaking research, active inference provides an integrated perspective on brain, cognition, and behavior that is increasingly used across multiple disciplines including neuroscience, psychology, and philosophy. Active inference puts the action into perception. This book offers the first comprehensive treatment of active inference, covering theory, applications, and cognitive domains. Active inference is a “first principles” approach to understanding behavior and the brain, framed in terms of a single imperative to minimize free energy. The book emphasizes the implications of the free energy principle for understanding how the brain works. It first introduces active inference both conceptually and formally, contextualizing it within current theories of cognition. It then provides specific examples of computational models that use active inference to explain such cognitive phenomena as perception, attention, memory, and planning.