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ECAI
2008
Springer
14 years 11 months ago
Learning in Planning with Temporally Extended Goals and Uncontrollable Events
Recent contributions to advancing planning from the classical model to more realistic problems include using temporal logic such as LTL to express desired properties of a solution ...
André A. Ciré, Adi Botea
AIPS
2009
14 years 11 months ago
Inference and Decomposition in Planning Using Causal Consistent Chains
Current state-of-the-art planners solve problems, easy and hard alike, by search, expanding hundreds or thousands of nodes. Yet, given the ability of people to solve easy problems...
Nir Lipovetzky, Hector Geffner
AIPS
2011
14 years 1 months ago
Sample-Based Planning for Continuous Action Markov Decision Processes
In this paper, we present a new algorithm that integrates recent advances in solving continuous bandit problems with sample-based rollout methods for planning in Markov Decision P...
Christopher R. Mansley, Ari Weinstein, Michael L. ...
ICTAI
2005
IEEE
15 years 3 months ago
Planning with POMDPs Using a Compact, Logic-Based Representation
Partially Observable Markov Decision Processes (POMDPs) provide a general framework for AI planning, but they lack the structure for representing real world planning problems in a...
Chenggang Wang, James G. Schmolze
UAI
2008
14 years 11 months ago
New Techniques for Algorithm Portfolio Design
We present and evaluate new techniques for designing algorithm portfolios. In our view, the problem has both a scheduling aspect and a machine learning aspect. Prior work has larg...
Matthew J. Streeter, Stephen F. Smith