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TOMACS
2010
79views more  TOMACS 2010»
13 years 2 months ago
A stochastic approximation method with max-norm projections and its applications to the Q-learning algorithm
In this paper, we develop a stochastic approximation method to solve a monotone estimation problem and use this method to enhance the empirical performance of the Q-learning algor...
Sumit Kunnumkal, Huseyin Topaloglu
STOC
2009
ACM
120views Algorithms» more  STOC 2009»
14 years 8 months ago
A constant-factor approximation for stochastic Steiner forest
We consider the stochastic Steiner forest problem: suppose we were given a collection of Steiner forest instances, and were guaranteed that a random one of these instances would a...
Anupam Gupta, Amit Kumar
WSC
2004
13 years 9 months ago
Stochastic Approximation with Simulated Annealing as an Approach to Global Discrete-Event Simulation Optimization
This paper explores an approach to global, stochastic, simulation optimization which combines stochastic approximation (SA) with simulated annealing (SAN). SA directs a search of ...
Matthew H. Jones, K. Preston White
FOCS
2004
IEEE
13 years 11 months ago
Approximating the Stochastic Knapsack Problem: The Benefit of Adaptivity
We consider a stochastic variant of the NP-hard 0/1 knapsack problem in which item values are deterministic and item sizes are independent random variables with known, arbitrary d...
Brian C. Dean, Michel X. Goemans, Jan Vondrá...
ATAL
2008
Springer
13 years 9 months ago
Stochastic search methods for nash equilibrium approximation in simulation-based games
We define the class of games called simulation-based games, in which the payoffs are available as an output of an oracle (simulator), rather than specified analytically or using a...
Yevgeniy Vorobeychik, Michael P. Wellman