Sciweavers

AIPS
1998
13 years 5 months ago
Solving Stochastic Planning Problems with Large State and Action Spaces
Planning methods for deterministic planning problems traditionally exploit factored representations to encode the dynamics of problems in terms of a set of parameters, e.g., the l...
Thomas Dean, Robert Givan, Kee-Eung Kim
IJCAI
2007
13 years 6 months ago
Average-Reward Decentralized Markov Decision Processes
Formal analysis of decentralized decision making has become a thriving research area in recent years, producing a number of multi-agent extensions of Markov decision processes. Wh...
Marek Petrik, Shlomo Zilberstein
IJCAI
2007
13 years 6 months ago
A Hybridized Planner for Stochastic Domains
Markov Decision Processes are a powerful framework for planning under uncertainty, but current algorithms have difficulties scaling to large problems. We present a novel probabil...
Mausam, Piergiorgio Bertoli, Daniel S. Weld
ATAL
2008
Springer
13 years 6 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
AIPS
2007
13 years 6 months ago
Prioritizing Bellman Backups without a Priority Queue
Several researchers have shown that the efficiency of value iteration, a dynamic programming algorithm for Markov decision processes, can be improved by prioritizing the order of...
Peng Dai, Eric A. Hansen
SARA
2005
Springer
13 years 10 months ago
Feature-Discovering Approximate Value Iteration Methods
Sets of features in Markov decision processes can play a critical role ximately representing value and in abstracting the state space. Selection of features is crucial to the succe...
Jia-Hong Wu, Robert Givan
QEST
2006
IEEE
13 years 10 months ago
LiQuor: A tool for Qualitative and Quantitative Linear Time analysis of Reactive Systems
LiQuor is a tool for verifying probabilistic reactive systems modelled Probmela programs, which are terms of a probabilistic guarded command language with an operational semantics...
Frank Ciesinski, Christel Baier
LICS
2009
IEEE
13 years 11 months ago
Statistic Analysis for Probabilistic Processes
—We associate a statistical vector to a trace and a geometrical embedding to a Markov Decision Process, based on a distance on words, and study basic Membership and Equivalence p...
Michel de Rougemont, Mathieu Tracol
ALT
2006
Springer
14 years 1 months ago
Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence
We address the problem of reinforcement learning in which observations may exhibit an arbitrary form of stochastic dependence on past observations and actions. The task for an age...
Daniil Ryabko, Marcus Hutter
VMCAI
2010
Springer
14 years 1 months ago
Best Probabilistic Transformers
This paper investigates relative precision and optimality of analyses for concurrent probabilistic systems. Aiming at the problem at the heart of probabilistic model checking ? com...
Björn Wachter, Lijun Zhang