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020 _a9783540877028
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024 7 _a10.1007/978-3-540-87702-8
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
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072 7 _aUYQ
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082 0 4 _a006.3
_223
245 1 4 _aThe Challenge of Anticipation
_h[electronic resource] :
_bA Unifying Framework for the Analysis and Design of Artificial Cognitive Systems /
_cedited by Giovanni Pezzulo, Martin V. Butz, Cristiano Castelfranchi, Rino Falcone.
250 _a1st ed. 2008.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2008.
300 _aXVI, 288 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v5225
505 0 _aTheory -- 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.
520 _aThis 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.
650 0 _aArtificial intelligence.
_93407
650 0 _aComputer programming.
_94169
650 0 _aComputer simulation.
_95106
650 0 _aComputer science.
_99832
650 0 _aComputer science
_xMathematics.
_93866
650 0 _aMathematical statistics.
_99597
650 0 _aUser interfaces (Computer systems).
_911681
650 0 _aHuman-computer interaction.
_96196
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aProgramming Techniques.
_9145204
650 2 4 _aComputer Modelling.
_9145205
650 2 4 _aModels of Computation.
_931806
650 2 4 _aProbability and Statistics in Computer Science.
_931857
650 2 4 _aUser Interfaces and Human Computer Interaction.
_931632
700 1 _aPezzulo, Giovanni.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9145206
700 1 _aButz, Martin V.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9145207
700 1 _aCastelfranchi, Cristiano.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9145208
700 1 _aFalcone, Rino.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_930902
710 2 _aSpringerLink (Online service)
_9145209
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540877011
776 0 8 _iPrinted edition:
_z9783540877240
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v5225
_9145210
856 4 0 _uhttps://doi.org/10.1007/978-3-540-87702-8
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