21 citations · 53 across the 15 of their papers we have counts for
6 papers · 1 filter
Adaptive Dialog Policy Learning with Hindsight and User Modeling
Yan Cao, Keting Lu, Xiaoping Chen +1
Reinforcement learning methods have been used to compute dialog policies from language-based interaction experiences. Efficiency is of particular importance in dialog policy learni…
Learning and Reasoning for Robot Dialog and Navigation Tasks
Keting Lu, Shiqi Zhang, Peter Stone +1
Reinforcement learning and probabilistic reasoning algorithms aim at learning from interaction experiences and reasoning with probabilistic contextual knowledge respectively. In th…
Robot Representation and Reasoning with Knowledge from Reinforcement Learning
Keting Lu, Shiqi Zhang, Peter Stone +1
Reinforcement learning (RL) agents aim at learning by interacting with an environment, and are not designed for representing or reasoning with declarative knowledge. Knowledge repr…
Goal-oriented Dialogue Policy Learning from Failures
Keting Lu, Shiqi Zhang, Xiaoping Chen
Reinforcement learning methods have been used for learning dialogue policies. However, learning an effective dialogue policy frequently requires prohibitively many conversations. T…
FHHOP: A Factored Hybrid Heuristic Online Planning Algorithm for Large POMDPs
Zhongzhang Zhang, Xiaoping Chen
Planning in partially observable Markov decision processes (POMDPs) remains a challenging topic in the artificial intelligence community, in spite of recent impressive progress in…
Rollout Sampling Policy Iteration for Decentralized POMDPs
Feng Wu, Shlomo Zilberstein, Xiaoping Chen
We present decentralized rollout sampling policy iteration (DecRSPI) - a new algorithm for multi-agent decision problems formalized as DEC-POMDPs. DecRSPI is designed to improve sc…