Cogent confabulation

被引:35
作者
Hecht-Nielsen, R [1 ]
机构
[1] Univ Calif San Diego, Dept Elect & Comp Engn, Inst Neural Computat, La Jolla, CA 92093 USA
关键词
vertebrate cognition; symbolic representations; attractor neural network; cogency; confabulation; duck test; inductive logic; Al;
D O I
10.1016/j.neunet.2004.11.003
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A new model of vertebrate cognition is introduced: maximization of cogency p(alpha beta gamma delta vertical bar epsilon). This model is shown to be a direct generalization of Aristotelian logic, and to be rigorously related to a calculable quantity. A key aspect of this model is that in Aristotelian logic information environments it functions logically. However, in non-Aristotelian environments, instead of finding the conclusion with the highest probability of being true (a popular past model of cognition); this model instead functions in the manner of the 'duck test;' by finding that conclusion which is most supportive of the truth of the assumed facts. (c) 2004 Elsevier Ltd. All rights reserved.
引用
收藏
页码:111 / 115
页数:5
相关论文
共 7 条
[1]  
Amit DJ, 1989, MODELING BRAIN FUNCT, DOI DOI 10.1017/CBO9780511623257
[2]   DISTINCTIVE FEATURES, CATEGORICAL PERCEPTION, AND PROBABILITY-LEARNING - SOME APPLICATIONS OF A NEURAL MODEL [J].
ANDERSON, JA ;
SILVERSTEIN, JW ;
RITZ, SA ;
JONES, RS .
PSYCHOLOGICAL REVIEW, 1977, 84 (05) :413-451
[3]  
[Anonymous], 2000, CAUSALITY
[4]  
Bender E. A., 2000, Mathematical Methods in Artificial Intelligence
[5]  
HECHTNIELSEN R, 2004, 0404 U CAL
[6]  
Nilsson N J., 1998, Artificial intelligence: a new synthesis
[7]   Improved bidirectional retrieval of sparse patterns stored by Hebbian learning [J].
Sommer, FT ;
Palm, G .
NEURAL NETWORKS, 1999, 12 (02) :281-297