We propose an agent-based behavioral model of pedestrians to improve tracking performance in realistic scenarios. In this model, we view pedestrians as decision-making agents who ...
Kota Yamaguchi, Alexander Berg, Luis Ortiz, Tamara...
We describe an approach to improving the naturalness of a social dialogue system, Talkie, by adding disfluencies and other content-independent enhancements to synthesized conversa...
Abstract— We propose a new approximate algorithm, LAJIV (Lookahead J-MDP Information Value), to solve Oracular Partially Observable Markov Decision Problems (OPOMDPs), a special ...
—A large amount of algorithms has recently been designed for the Internet under the assumption that the distance defined by the round-trip delay (RTT) is a metric. Moreover, man...
Pierre Fraigniaud, Emmanuelle Lebhar, Laurent Vien...
Multiagent Partially Observable Markov Decision Processes are a popular model of multiagent systems with uncertainty. Since the computational cost for finding an optimal joint pol...