Abstract-- We introduce a distributed estimation algorithm for use by a collection of stochastically interacting agents. Each agent has both a discrete value and an estimate of the...
We consider here the problem of building a never-ending language learner; that is, an intelligent computer agent that runs forever and that each day must (1) extract, or read, inf...
Andrew Carlson, Justin Betteridge, Bryan Kisiel, B...
Abstract This paper presents and discusses a novel approach to indeterministic belief revision. An indeterministic belief revision operator assumes that, when an agent is confronte...
We propose novel gaze control algorithms for active perception in mobile autonomous agents with directable, foveated vision sensors. Our agents are realistic artificial animals, o...
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...