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AAAI
2006
13 years 5 months ago
Improving Approximate Value Iteration Using Memories and Predictive State Representations
Planning in partially-observable dynamical systems is a challenging problem, and recent developments in point-based techniques such as Perseus significantly improve performance as...
Michael R. James, Ton Wessling, Nikos A. Vlassis
IWMM
2010
Springer
118views Hardware» more  IWMM 2010»
13 years 8 months ago
Speculative parallelization using state separation and multiple value prediction
With the availability of chip multiprocessor (CMP) and simultaneous multithreading (SMT) machines, extracting thread level parallelism from a sequential program has become crucial...
Chen Tian, Min Feng, Rajiv Gupta
SARA
2005
Springer
13 years 9 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
IJCAI
2003
13 years 5 months ago
Approximate Policy Iteration using Large-Margin Classifiers
We present an approximate policy iteration algorithm that uses rollouts to estimate the value of each action under a given policy in a subset of states and a classifier to general...
Michail G. Lagoudakis, Ronald Parr
AAAI
2006
13 years 5 months ago
Functional Value Iteration for Decision-Theoretic Planning with General Utility Functions
We study how to find plans that maximize the expected total utility for a given MDP, a planning objective that is important for decision making in high-stakes domains. The optimal...
Yaxin Liu, Sven Koenig