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AAAI
2007
15 years 5 months ago
Stochastic Optimization for Collision Selection in High Energy Physics
Artificial intelligence has begun to play a critical role in basic science research. In high energy physics, AI methods can aid precision measurements that elucidate the underlyi...
Shimon Whiteson, Daniel Whiteson
PRIMA
2009
Springer
15 years 10 months ago
Recursive Adaptation of Stepsize Parameter for Non-stationary Environments
In this article, we propose a method to adapt stepsize parameters used in reinforcement learning for dynamic environments. In general reinforcement learning situations, a stepsize...
Itsuki Noda
134
Voted
AAAI
1998
15 years 4 months ago
Solving Very Large Weakly Coupled Markov Decision Processes
We present a technique for computing approximately optimal solutions to stochastic resource allocation problems modeled as Markov decision processes (MDPs). We exploit two key pro...
Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, L...
119
Voted
IAT
2003
IEEE
15 years 8 months ago
MPIAB: A Novel Agent Architecture for Parallel Processing
This paper presents MPIAB, an agent based architecture for parallel processing. The architecture is developed to model the functions of standard MPI using java agents. It remedies...
Shahram Rahimi, Ajay Narayanan, Meha Sabharwal
ICML
2005
IEEE
16 years 4 months ago
Bayesian sparse sampling for on-line reward optimization
We present an efficient "sparse sampling" technique for approximating Bayes optimal decision making in reinforcement learning, addressing the well known exploration vers...
Tao Wang, Daniel J. Lizotte, Michael H. Bowling, D...