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» Learning action effects in partially observable domains
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ATAL
2008
Springer
14 years 11 months ago
Continual collaborative planning for mixed-initiative action and interaction
Multiagent environments are often highly dynamic and only partially observable which makes deliberative action planning computationally hard. In many such environments, however, a...
Michael Brenner
AINA
2007
IEEE
15 years 1 months ago
Domain Modelling for Ubiquitous Computing Applications
Many Ubiquitous computing applications can be considered as planning and acting problems in environments characterised by uncertainty and partial observability. Such systems rely ...
Anthony Harrington, Vinny Cahill
WEBI
2009
Springer
15 years 4 months ago
Adapting Reinforcement Learning for Trust: Effective Modeling in Dynamic Environments
—In open multiagent systems, agents need to model their environments in order to identify trustworthy agents. Models of the environment should be accurate so that decisions about...
Özgür Kafali, Pinar Yolum
ICCV
2011
IEEE
13 years 9 months ago
Dynamic Manifold Warping for View Invariant Action Recognition
We address the problem of learning view-invariant 3D models of human motion from motion capture data, in order to recognize human actions from a monocular video sequence with arbi...
Dian Gong, Gerard Medioni
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ECML
2007
Springer
15 years 3 months ago
Safe Q-Learning on Complete History Spaces
In this article, we present an idea for solving deterministic partially observable markov decision processes (POMDPs) based on a history space containing sequences of past observat...
Stephan Timmer, Martin Riedmiller