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AAAI
2006
13 years 8 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 11 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
14 years 14 days 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 8 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 8 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