Young children demonstrate the ability to make inferences about the preferences of other agents based on their choices. However, there exists no overarching account of what childr...
Christopher G. Lucas, Thomas L. Griffiths, Fei Xu,...
This paper describes DIDO, a system we have developed to carry out exploratory learning of unfamiliar domains without assistance from an external teacher. The program incorporates...
Abstract. In this paper we present a Reinforcement Learning (RL) approach with the capability to train neural adaptive controllers for complex control problems without expensive on...
Hidden Markov models hmms and partially observable Markov decision processes pomdps provide useful tools for modeling dynamical systems. They are particularly useful for represent...
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...