• 연사: Prof. Henry Liberman
  • 소속: MIT
  • 초록: Despite all the recent successes of AI, computers still struggle to capture simple knowledge about people and everyday life — what we call “commonsense” knowledge. Commonsense knowledge underlies our ability to understand language and perform problem solving. Commonsense knowledge is different from “factual” knowledge, as you might find in Wikipedia or encyclopedias. Commonsense reasoning is also different from probabilistic reasoning, as humans (as far as we know) perform commonsense reasoning without the counting operations inherent in probability. Commonsense reasoning is about plausibility rather than truth per se, and is best performed by analogical reasoning. I will describe efforts to collect commonsense knowledge, to reason with it, and to synthesize both commonsense and probabilistic approaches. Commonsense knowledge is important in user interfaces for intelligent agents, for sensible default behavior for interfaces, and for explanation and debugging.

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