The Challenge of Anticipation A Unifying Framework for the Analysis and Design of Artificial Cognitive Systems / [electronic resource] :
edited by Giovanni Pezzulo, Martin V. Butz, Cristiano Castelfranchi, Rino Falcone.
- 1st ed. 2008.
- XVI, 288 p. online resource.
- Lecture Notes in Artificial Intelligence, 5225 2945-9141 ; .
- Lecture Notes in Artificial Intelligence, 5225 .
Theory -- Introduction: Anticipation in Natural and Artificial Cognition -- The Anticipatory Approach: Definitions and Taxonomies -- Benefits of Anticipations in Cognitive Agents -- Models, Architectures, and Applications -- Anticipation in Attention -- Anticipatory, Goal-Directed Behavior -- Anticipation and Believability -- Anticipation and Emotions for Goal Directed Agents -- A Reinforcement-Learning Model of Top-Down Attention Based on a Potential-Action Map -- Anticipation by Analogy -- Anticipation in Coordination -- Endowing Artificial Systems with Anticipatory Capabilities: Success Cases.
This book proposes a unifying approach for the analysis and design of artificial cognitive systems: The Anticipatory Approach. In 11 coherent chapters, the authors of this State-of-the-Art Survey propose a foundational view of the importance of dealing with the future, of gaining some autonomy from current environmental data, and of endogenously generating sensorimotor and abstract representations. A meaningful taxonomy for anticipatory cognitive mechanisms is put forward, which distinguishes between the types of predictions and the different influences of these predictions on actual behavior and learning. Thus a new unifying perspective on cognitive systems is given. The Anticipatory Approach described in this book will not only aid in the analysis of cognitive systems, but will also serve as an inspiration and guideline for the progressively more advanced and competent design of large, but modular, artificial cognitive systems.
9783540877028
10.1007/978-3-540-87702-8 doi
Artificial intelligence. Computer programming. Computer simulation. Computer science. Computer science--Mathematics. Mathematical statistics. User interfaces (Computer systems). Human-computer interaction. Artificial Intelligence. Programming Techniques. Computer Modelling. Models of Computation. Probability and Statistics in Computer Science. User Interfaces and Human Computer Interaction.