The Challenge of Anticipation

1. Front Matter

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2. Theory

   1. Front Matter

      Pages 1-1

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   2. Introduction: Anticipation in Natural and Artificial Cognition

      • Giovanni Pezzulo, Martin V. Butz, Cristiano Castelfranchi, Rino Falcone

      Pages 3-22

   3. The Anticipatory Approach: Definitions and Taxonomies

      • Giovanni Pezzulo, Martin V. Butz, Cristiano Castelfranchi

      Pages 23-43

   4. Benefits of Anticipations in Cognitive Agents

      • Martin V. Butz, Giovanni Pezzulo

      Pages 45-62

3. Models, Architectures, and Applications

   1. Front Matter

      Pages 63-63

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   2. Anticipation in Attention

      • Christian Balkenius, Alexander Förster, Birger Johansson, Vin Thorsteinsdottir

      Pages 65-83

   3. Anticipatory, Goal-Directed Behavior

      • Martin V. Butz, Oliver Herbort, Giovanni Pezzulo

      Pages 85-113

   4. Anticipation and Believability

      • Carlos Martinho, Ana Paiva

      Pages 115-133

   5. Anticipation and Emotions for Goal Directed Agents

      • Emiliano Lorini, Michele Piunti, Cristiano Castelfranchi, Rino Falcone, Maria Miceli

      Pages 135-160

   6. A Reinforcement-Learning Model of Top-Down Attention Based on a Potential-Action Map

      • Dimitri Ognibene, Christian Balkenius, Gianluca Baldassarre

      Pages 161-184

   7. Anticipation by Analogy

      • Boicho Kokinov, Maurice Grinberg, Georgi Petkov, Kiril Kiryazov

      Pages 185-213

   8. Anticipation in Coordination

      • Maurice Grinberg, Emilian Lalev

      Pages 215-236

   9. Endowing Artificial Systems with Anticipatory Capabilities: Success Cases

      • Giovanni Pezzulo, Martin V. Butz, Cristiano Castelfranchi, Rino Falcone, Gianluca Baldassarre, Christian Balkenius et al.

      Pages 237-254

4. Back Matter

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The general idea that brains anticipate the future, that they engage in prediction, and that one means of doing this is through some sort of inner model that can be run of?ine,hasalonghistory. SomeversionoftheideawascommontoAristotle,aswell as to many medieval scholastics, to Leibniz and Hume, and in more recent times, to Kenneth Craik and Philip Johnson-Laird. One reason that this general idea recurs continually is that this is the kind of picture that introspection paints. When we are engaged in tasks it seems that we form images that are predictions, or anticipations, and that these images are isomorphic to what they represent. But as much as the general idea recurs, opposition to it also recurs. The idea has never been widely accepted, or uncontroversial among psychologists, cognitive scientists and neuroscientists. The main reason has been that science cannot be s- is?ed with metaphors and introspection. In order to gain acceptance, an idea needs to be formulated clearly enough so that it can be used to construct testable hypot- ses whose results will clearly supportor cast doubtupon the hypothesis. Next, those ideasthatare formulablein one oranothersortof symbolismor notationare capable of being modeled, and modeling is a huge part of cognitive neuroscience. If an idea cannot be clearly modeled, then there are limits to how widely it can be tested and accepted by a cognitive neuroscience community.

• Design
• Emotion
• agents
• anticipation
• atrificial cognition
• believability
• calculus
• cognition
• cognitive systems
• goal-oriented
• inverse model
• learning
• learningmodelling
• model
• prediction

• Istituto di Scienze e Tecnologie della Cognizione - CNR, Rome, Italy

  Giovanni Pezzulo, Cristiano Castelfranchi, Rino Falcone

• Institut für Psychologie, Kognitive Psychologie III, Universität Würzburg, Würzburg, Germany

  Martin V. Butz

Policies and ethics