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AAAI
2012
6 years 10 months ago
Kernel-Based Reinforcement Learning on Representative States
Markov decision processes (MDPs) are an established framework for solving sequential decision-making problems under uncertainty. In this work, we propose a new method for batchmod...
Branislav Kveton, Georgios Theocharous
CORR
2012
Springer
286views Education» more  CORR 2012»
7 years 4 months ago
A Faster Algorithm for Solving One-Clock Priced Timed Games
One-clock priced timed games is a class of two-player, zero-sum, continuous-time games that was defined and thoroughly studied in previous works. We show that One-clock priced ti...
Thomas Dueholm Hansen, Rasmus Ibsen-Jensen, Peter ...

Publication
151views
7 years 6 months ago
Robust Bayesian reinforcement learning through tight lower bounds
In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinfo...
Christos Dimitrakakis

Publication
233views
7 years 6 months ago
Sparse reward processes
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
Christos Dimitrakakis
ATAL
2011
Springer
7 years 8 months ago
Towards a unifying characterization for quantifying weak coupling in dec-POMDPs
Researchers in the field of multiagent sequential decision making have commonly used the terms “weakly-coupled” and “loosely-coupled” to qualitatively classify problems i...
Stefan J. Witwicki, Edmund H. Durfee
IWQOS
2011
Springer
7 years 11 months ago
An MDP-based admission control for a QoS-aware service-oriented system
In this paper, we address the problem of providing a service broker, which offers to prospective users a composite service with a range of different Quality of Service (QoS) class...
Marco Abundo, Valeria Cardellini, Francesco Lo Pre...
AIPS
2011
7 years 12 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. ...
AAAI
1994
8 years 9 months ago
Control Strategies for a Stochastic Planner
We present new algorithms for local planning over Markov decision processes. The base-level algorithm possesses several interesting features for control of computation, based on s...
Jonathan Tash, Stuart J. Russell
UAI
2000
8 years 9 months ago
The Complexity of Decentralized Control of Markov Decision Processes
We consider decentralized control of Markov decision processes and give complexity bounds on the worst-case running time for algorithms that find optimal solutions. Generalization...
Daniel S. Bernstein, Shlomo Zilberstein, Neil Imme...
UAI
1998
8 years 9 months ago
Hierarchical Solution of Markov Decision Processes using Macro-actions
tigate the use of temporally abstract actions, or macro-actions, in the solution of Markov decision processes. Unlike current models that combine both primitive actions and macro-...
Milos Hauskrecht, Nicolas Meuleau, Leslie Pack Kae...
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