L.F. Fass (USA)
Artificial intelligence, theoretical foundations, cognition, learning.
Language is such an important component and indicator of intelligence that results from the field of “language learning” can be applied throughout knowledge-discovery and knowledge-acquisition research domains. Our theory based research and “lessons learned” show that specific results in language learning can be applied in generalized machine (AI) and human (CogSci) learning. Perfect learning and processing may not be achievable in the practical real world, but our formal results provide a foundation for realistic, acceptable approximations. Adap tation to better approximations illustrates intelligence. We compare findings with related work of other researchers, involving: learning by situated agents; automated voice recognition; and comparisons of learning by autistics and by programmed intelligent systems. We conclude AI and CogSci can learn alot from “language learning”.
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