Predictive state representations (PSRs) have recently been proposed as an alternative to partially observable Markov decision processes (POMDPs) for representing the state of a dy...
Matthew Rosencrantz, Geoffrey J. Gordon, Sebastian...
In this paper, we propose to use 3D information to augment the Markov random field (MRF) model for object recognition. Conventional MRF for image-based object recognition usually ...
Wei Yu, Ahmed Bilal Ashraf, Yao-Jen Chang, Congcon...
Multi-agent systems are an increasingly important software paradigm and in many of its applications agents cooperate to achieve a particular goal. This requires the design of effi...
Taolue Chen, Marta Z. Kwiatkowska, David Parker, A...
The progressive processing model allows a system to trade off resource consumption against the quality of the outcome by mapping each activity to a graph of potential solution met...
The goal of Reinforcement learning (RL) is to maximize reward (minimize cost) in a Markov decision process (MDP) without knowing the underlying model a priori. RL algorithms tend ...