We present several new algorithms for multiagent reinforcement learning. A common feature of these algorithms is a parameterized, structured representation of a policy or value fu...
Carlos Guestrin, Michail G. Lagoudakis, Ronald Par...
Policy Reuse is a reinforcement learning technique that efficiently learns a new policy by using past similar learned policies. The Policy Reuse learner improves its exploration b...
Compared to optimal planners, satisficing planners can solve much harder problems but may produce overly costly and long plans. Plan quality for satisficing planners has become in...
Planning methods for deterministic planning problems traditionally exploit factored representations to encode the dynamics of problems in terms of a set of parameters, e.g., the l...
The problem of recognizing actions in realistic videos
is challenging yet absorbing owing to its great potentials
in many practical applications. Most previous research is
limit...
Jintao Li, Ju Sun, Loong Fah Cheong, Shuicheng Yan...