3 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.AI2019★ 3 cited
Online Learning and Planning in Partially Observable Domains without Prior Knowledge
Yunlong Liu, Jianyang Zheng
How an agent can act optimally in stochastic, partially observable domains is a challenge problem, the standard approach to address this issue is to learn the domain model firstly…
cs.AI2019★ 1 cited
Combining Offline Models and Online Monte-Carlo Tree Search for Planning from Scratch
Yunlong Liu, Jianyang Zheng
Planning in stochastic and partially observable environments is a central issue in artificial intelligence. One commonly used technique for solving such a problem is by constructin…