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» Learning Partially Observable Deterministic Action Models
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ICST
2009
IEEE
13 years 5 months ago
Timed Testing under Partial Observability
This paper studies the problem of model-based testing of real-time systems that are only partially observable. We model the System Under Test (SUT) using Timed Game Automata (TGA)...
Alexandre David, Kim Guldstrand Larsen, Shuhao Li,...
ATAL
2008
Springer
13 years 9 months ago
Reinforcement learning for DEC-MDPs with changing action sets and partially ordered dependencies
Decentralized Markov decision processes are frequently used to model cooperative multi-agent systems. In this paper, we identify a subclass of general DEC-MDPs that features regul...
Thomas Gabel, Martin A. Riedmiller
AAAI
1996
13 years 9 months ago
Computing Optimal Policies for Partially Observable Decision Processes Using Compact Representations
: Partially-observable Markov decision processes provide a very general model for decision-theoretic planning problems, allowing the trade-offs between various courses of actions t...
Craig Boutilier, David Poole
CVPR
2008
IEEE
14 years 9 months ago
Learning 4D action feature models for arbitrary view action recognition
In this paper we present a novel approach using a 4D (x,y,z,t) action feature model (4D-AFM) for recognizing actions from arbitrary views. The 4D-AFM elegantly encodes shape and m...
Pingkun Yan, Saad M. Khan, Mubarak Shah
CORR
2011
Springer
161views Education» more  CORR 2011»
12 years 11 months ago
Doubly Robust Policy Evaluation and Learning
We study decision making in environments where the reward is only partially observed, but can be modeled as a function of an action and an observed context. This setting, known as...
Miroslav Dudík, John Langford, Lihong Li