250 search results - page 20 / 50 » Learning action effects in partially observable domains |
PKDD
2009
Springer
15 years 4 months ago
2009
Springer
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
ICCV
2007
IEEE
15 years 4 months ago
2007
IEEE
In this paper, we address the problem of learning compact, view-independent, realistic 3D models of human actions recorded with multiple cameras, for the purpose of recognizing th...
81
Voted
NIPS
2003
14 years 11 months ago
2003
In large multiagent games, partial observability, coordination, and credit assignment persistently plague attempts to design good learning algorithms. We provide a simple and efï¬...
AAAI
2012
13 years 19 hour ago
2012
Recent work on planning in incomplete domains focuses on constructing plans that succeed despite incomplete knowledge of action preconditions and effects. As planning models becom...
IICAI
2007
14 years 11 months ago
2007
Logics of action, for reasoning about the effects of state change, and logics of belief, accounting for belief revision and update, have much in common. Furthermore, we may underta...