AAAI Publications, Twenty-Eighth AAAI Conference on Artificial Intelligence

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Learning Unknown Event Models
Matthew Molineaux, David W. Aha

Last modified: 2014-06-19


Agents with incomplete environment models are likely to be surprised, and this represents an opportunity to learn. We investigate approaches for situated agents to detect surprises, discriminate among different forms of surprise, and hypothesize new models for the unknown events that surprised them. We instantiate these approaches in a new goal reasoning agent (named FoolMeTwice), investigate its performance in simulation studies, and report that it produces plans with significantly reduced execution cost in comparison to not learning models for surprising events.


relational learning; learning of environment models; exogenous event models;

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