Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
Approximate dynamic programming has been used successfully in a large variety of domains, but it relies on a small set of provided approximation features to calculate solutions re...
Marek Petrik, Gavin Taylor, Ronald Parr, Shlomo Zi...
Magnifying Lens Abstraction in Markov Decision Processes ∗ Pritam Roy1 David Parker2 Gethin Norman2 Luca de Alfaro1 Computer Engineering Dept, UC Santa Cruz, Santa Cruz, CA, USA ...
Pritam Roy, David Parker, Gethin Norman, Luca de A...
Decentralized Markov Decision Processes (DEC-MDPs) are a popular model of agent-coordination problems in domains with uncertainty and time constraints but very difficult to solve...
—This paper presents a method for learning decision theoretic models of human behaviors from video data. Our system learns relationships between the movements of a person, the co...