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IJCAI
2001
15 years 7 months ago
R-MAX - A General Polynomial Time Algorithm for Near-Optimal Reinforcement Learning
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
Ronen I. Brafman, Moshe Tennenholtz
180
Voted
NIPS
2003
15 years 7 months ago
A Nonlinear Predictive State Representation
Predictive state representations (PSRs) use predictions of a set of tests to represent the state of controlled dynamical systems. One reason why this representation is exciting as...
Matthew R. Rudary, Satinder P. Singh
GRAPHICSINTERFACE
2000
15 years 7 months ago
Are We All In the Same "Bloat"?
"Bloat", a term that has existed in the technical community for many years, has recently received attention in the popular press. The term has a negative connotation imp...
Joanna McGrenere, Gale Moore
IPCO
1998
99views Optimization» more  IPCO 1998»
15 years 7 months ago
Non-approximability Results for Scheduling Problems with Minsum Criteria
We provide several non-approximability results for deterministic scheduling problems whose objective is to minimize the total job completion time. Unless P = NP, none of the probl...
Han Hoogeveen, Petra Schuurman, Gerhard J. Woeging...
178
Voted
IJCAI
1989
15 years 7 months ago
Constrained Heuristic Search
Cognitive architectures aspire for generality both in terms of problem solving and learning across a range of problems, yet to date few examples of domain independent learning has...
Mark S. Fox, Norman M. Sadeh, Can A. Baykan