This article advocates a new model for inductive learning. Called sequential induction, it helps bridge classical fixed-sample learning techniques (which are efficient but difficu...
We formalize a model for supervised learning of action strategies in dynamic stochastic domains and show that PAC-learning results on Occam algorithms hold in this model as well. W...
In this article we present a novel, hybrid graph spatial representation for robot navigation. This representation enables our mobile robot to build a model of its surroundings whi...
We describe a program, BEATRIX, that can understand textbook physics problems specified by a combination of English text and a diagram. The result of the understanding process is ...
Empirical analyses of complex games necessarily focus on a restricted set of strategies, and thus the value of empirical game models depends on effective methods for selectively e...
Patrick R. Jordan, L. Julian Schvartzman, Michael ...