PRIMATE COGNITION - COMPARING PROBLEMS AND SKILLS

被引:22
作者
BYRNE, RW
机构
[1] Scottish Primate Research Group, Department of Psychology, University of St. Andrews, St. Andrews, Fife
关键词
PRIMATES; EVOLUTION; COGNITION; INTELLIGENCE; COMPLEXITY; BRAIN SIZE;
D O I
10.1002/ajp.1350370206
中图分类号
Q95 [动物学];
学科分类号
071002 ;
摘要
Primate cognition is believed to have adapted during evolution in response to complexity, stemming from either social or environmental challenges. Arguments favoring one or another domain as the predominant spur to increased intelligence have been proposed on the basis of the inherent complexity of problems facing primates and the sophistication of their observed behavioral response. A review of recent findings shows that cognitive differences between primates are well revealed by naturally posed problems. Current evidence shows a sensitivity to fine social distinctions in haplorhine primates, associated with complex social manipulations and neocortical enlargement, compared to strepsirhines. Several aspects of foraging behavior also suggests cognitive sophistication in various primates. Depth of understanding, however, is greater in great apes than in monkeys; this applies to both spheres, social (e.g., comprehending mental states) and nonsocial (e.g., comprehending physical mechanism and hierarchical organization of behavior). The increased representational understanding in great apes is not associated either with more manipulative social actions or with neocortical enlargement, compared to monkeys. This evidence supports theories of a social origin of cognition for those aspects shared by monkeys and apes but not for the unique qualitative differences of great apes. Task complexity is difficult, perhaps impossible, to measure or compare across domains; any such comparison would certainly be premature at present for primates. Behavioral skill, though in principle simpler to compare, is at present difficult to assess when there is no common currency of theory-building. With the aim of encouraging comparisons of data from laboratory and field and from social and technical problems, a preliminary exploration is made with a notation derived from artificial intelligence; this is shown to be capable of representing theories of complex behavior in both social and technical domains. (C) 1995 Wiley-Liss, Inc.
引用
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页码:127 / 141
页数:15
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