ISSN:
1572-8641
Keywords:
Representation
;
cognitive architecture
;
concepts
;
machine learning
;
game playing
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
,
Philosophy
Notes:
Abstract The extent to which concepts, memory, and planning are necessary to the simulation of intelligent behavior is a fundamental philosophical issue in Artificial Intelligence. An active and productive segement of the AI community has taken the position that multiple low-level agents, properly organized, can account for high-level behavior. Empirical research on these questions with fully operational systems has been restricted to mobile robots that do simple tasks. This paper recounts experiments with Hoyle, a system in a cerebral, rather than a physical, domain. The program learns to perform well and quickly, often outpacing its human creators at two-person, perfect information board games. Hoyle demonstrates that a surprising amount of intelligent behavior can be treated as if it were situation-determined, that often planning is unnecessary, and that the memory required to support this learning is minimal. Concepts, however, are crucial to this reactive program's ability to learn and perform.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF02454222
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