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Associative Memory-based Reasoning: a Computational Model of Analogy-making in a Decentralized Multi-agent Cognitive Architecture Alexander A. Petrov
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Associative Memory-based Reasoning: a Computational Model of Analogy-making in a Decentralized Multi-agent Cognitive Architecture
Alexander A. Petrov
Through analogy, novel situations and problems can be understood in terms of familiar ones. There is converging evidence that analogy-making lies at the very core of human cognition. Conversely, successful analogy-making requires the resources of an entire cognitive architecture. This book describes a computational model of analogy-making called AMBR (Associative Memory-Based Reasoning). AMBR is based on a hybrid symbolic-connectionist multi-agent cognitive architecture called DUAL. Macroscopic behavior in DUAL emerges from the interactions of simple processing agents in dynamic coalitions. Unlike the mainstream models of analogy-making, AMBR uses a decentralized representational scheme for problems and situations. The dynamic emergent processing of these decentralized representations is consistent with the context-sensitive and constructive nature of human memory. Both DUAL and AMBR were developed by Boicho N. Kokinov and his graduate students at New Bulgarian University. This book is a revised and expanded version of the author's Ph. D. thesis written under Prof. Kokinov's supervision at NBU. It will be of interest to cognitive modelers and cognitive scientists more generally.
| メディア | 書籍 Paperback Book (ソフトカバーで背表紙を接着した本) |
| リリース済み | 2013年11月1日 |
| ISBN13 | 9783659262487 |
| 出版社 | LAP LAMBERT Academic Publishing |
| ページ数 | 212 |
| 寸法 | 152 × 229 × 12 mm · 334 g |
| 言語 | ドイツ語 |