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» Ranking policies in discrete Markov decision processes
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AAAI
2006
13 years 9 months ago
Decision Making in Uncertain Real-World Domains Using DT-Golog
DTGolog, a decision-theoretic agent programming language based on the situation calculus, was proposed to ease some of the computational difficulties associated with Markov Decisi...
Mikhail Soutchanski, Huy Pham, John Mylopoulos
ICC
2008
IEEE
169views Communications» more  ICC 2008»
14 years 2 months ago
Optimality of Myopic Sensing in Multi-Channel Opportunistic Access
—We consider opportunistic communications over multiple channels where the state (“good” or “bad”) of each channel evolves as independent and identically distributed Mark...
Tara Javidi, Bhaskar Krishnamachari, Qing Zhao, Mi...
ICRA
2010
IEEE
163views Robotics» more  ICRA 2010»
13 years 6 months ago
Exploiting domain knowledge in planning for uncertain robot systems modeled as POMDPs
Abstract— We propose a planning algorithm that allows usersupplied domain knowledge to be exploited in the synthesis of information feedback policies for systems modeled as parti...
Salvatore Candido, James C. Davidson, Seth Hutchin...
AAAI
2006
13 years 9 months ago
Targeting Specific Distributions of Trajectories in MDPs
We define TTD-MDPs, a novel class of Markov decision processes where the traditional goal of an agent is changed from finding an optimal trajectory through a state space to realiz...
David L. Roberts, Mark J. Nelson, Charles Lee Isbe...
ICRA
2010
IEEE
143views Robotics» more  ICRA 2010»
13 years 6 months ago
Apprenticeship learning via soft local homomorphisms
Abstract— We consider the problem of apprenticeship learning when the expert’s demonstration covers only a small part of a large state space. Inverse Reinforcement Learning (IR...
Abdeslam Boularias, Brahim Chaib-draa