Motivating the 2006 AAAI Spring Symposium: Cognitive Science Principles Meet AI-Hard Problems.
Christian J. Lebiere, Robert E. Wray · National Conference on Artificial Intelligence · 2006
Artificial Intelligence and Cognitive Science have always been overlapping disciplines. Early in their history, that overlap was considerable. Herbert A. Simon wrote that “AI can have two purposes. One is to use the power of computers to augment human thinking. ... The other is to use a computer’s artificial intelligence to understand how humans think.” Conversely, at the foundation of the Cognitive Science Society, Artificial Intelligence was identified as one of the core constituent disciplines. However, over time the two disciplines have increasingly diverged under seemingly incompatible constraints. The difficulty of many problems tackled by AI led it to adopt brute-force or domain-specific solutions that arguably were not cognitively plausible and did not generalize well to other problems. Conversely, the need for precision and reproducibility increasingly led cognitive science to focus on experimental paradigms that AI did not recognize as hard problems. Recently, in his AAAI presidential address, Tom Mitchell called for a rapprochement between the two disciplines on the basis of convergent evolution (Mitchell, 2002).