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LEADER 00000cam  2200661Ii 4500 
001    288585999 
003    OCoLC 
005    20181101051306.4 
006    m     o  d         
007    cr cn||||||||| 
008    081217s2008    gw a    ob    000 0 eng d 
010    2008934765 
019    288960432|a646764581|a698465660|a767210162|a777966494
020    9783540877028 
020    3540877029 
020    |z9783540877011|q(paper) 
020    |z3540877010|q(paper) 
024 7  10.1007/978-3-540-87702-8|2doi 
035    (OCoLC)288585999|z(OCoLC)288960432|z(OCoLC)646764581
037    978-3-540-87701-1|bSpringer|n 
040    GW5XE|beng|epn|erda|cGW5XE|dEMU|dUMC|dKKS|dW2U|dOCLCQ
049    MAIN 
050  4 QP360.5|b.C43 2008eb 
072  7 UYQ|2bicssc 
072  7 TJFM1|2bicssc 
072  7 COM004000|2bisacsh 
082 04 612.8/2|222 
245 04 The challenge of anticipation :|ba unifying framework for 
       the analysis and design of artificial cognitive systems /
       |cGiovanni Pezzulo [and others] (eds.). 
264  1 Berlin ;|aNew York :|bSpringer,|c2008. 
300    1 online resource (xvi, 288 pages) :|billustrations. 
336    text|btxt|2rdacontent 
337    computer|bc|2rdamedia 
338    online resource|bcr|2rdacarrier 
340    |gpolychrome|2rdacc|0
490 1  Lecture notes in artificial intelligence, subseries of 
       Lecture notes in computer science,|x0302-9743 ;|v5225 
490 1  State-of-the-art survey 
490 1  LNCS sublibrary. SL 7, Artificial intelligence. 
504    Includes bibliographical references (pages 255-288). 
505 00 |tIntroduction: Anticipation in natural and artificial 
       cognition /|rGiovanni Pezzulo [and others] --|tThe 
       anticipatory approach: definitions and taxonomies /
       |rGiovanni Pezzulo, Martin V. Butz and Cristiano 
       Castelfranchi --|tBenefits of anticipations in cognitive 
       agents /|rMartin V. Butz and Giovanni Pezzulo --
       |tAnticipation in attention /|rChristian Balkenius [and 
       others] --|tAnticipatory, goal-directed behavior /|rMartin
       V. Butz, Oliver Herbort and Giovanni Pezzulo --
       |tAnticipation and believability /|rCarlos Martinho and 
       Ana Paiva --|tAnticipation and emotions for goal directed 
       agents /|rEmiliano Lorini [and others] --|tA reinforcement
       -learning model of top-down attention based on a potential
       -action map /|rDimitri Ognibene, Christian Balkenius and 
       Gianluca Baldassarre --|tAnticipation by analogy /|rBoicho
       Kokinov [and others] --|tAnticipation in coordination /
       |rMaurice Grinberg and Emilian Lalev --|tEndowing 
       artificial systems with anticipatory capabilities: success
       cases /|rGiovanni Pezzulo [and others]. 
520    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. 
588 0  Print version record. 
650  0 Expectation (Psychology)|0
       subjects/sh85046420|xMathematical models.|0http:// 
650  0 Cognitive learning theory|0
       subjects/sh91005035|xMathematical models.|0http:// 
650  0 Cognitive neuroscience|0
       subjects/sh91005166|xMathematical models.|0http:// 
650  0 Brain|xMathematical models.|0
655  4 Electronic books. 
700 1  Pezzulo, Giovanni.|0
776 08 |iPrint version:|tChallenge of anticipation.|dBerlin ; New
       York : Springer, 2008|z9783540877011|z3540877010
830  0 Lecture notes in computer science ;|0
830  0 Lecture notes in computer science.|pLecture notes in 
       artificial intelligence.|0
830  0 Lecture notes in computer science.|pState-of-the-art 
830  0 LNCS sublibrary.|nSL 7,|pArtificial intelligence.|0http:// 
912    .b15029979JOHNC 
990    SpringerLink|bSpringer English/International eBooks 2008 -
       Full Set|c2018-10-31|yNew collection 
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