Partially observable Markov decision processes (POMDPs) are an intuitive and general way to model sequential decision making problems under uncertainty. Unfortunately, even approx...
Tao Wang, Pascal Poupart, Michael H. Bowling, Dale...
We present a probabilistic method for path planning that considers trajectories constrained by both the environment and an ensemble of restrictions or preferences on preferred mot...
Variants of the decentralized MDP model focus on problems exhibiting some special structure that makes them easier to solve in practice. Our work is concerned with two main issues...
Autonomousagentsin the real world must be capableof asynchronous goal generation. However, one consequence of this ability is that the agent may generate a substantial number of go...
The information resources on the Web are vast, but much of the Web is based on a browsing paradigm that requires someone to actively seek information. Instead, one would like to h...