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GECCO
2008
Springer
183views Optimization» more  GECCO 2008»
13 years 8 months ago
UMDAs for dynamic optimization problems
This paper investigates how the Univariate Marginal Distribution Algorithm (UMDA) behaves in non-stationary environments when engaging in sampling and selection strategies designe...
Carlos M. Fernandes, Cláudio F. Lima, Agost...
WSC
2007
13 years 9 months ago
Stochastic trust region gradient-free method (strong): a new response-surface-based algorithm in simulation optimization
Response Surface Methodology (RSM) is a metamodelbased optimization method. Its strategy is to explore small subregions of the parameter space in succession instead of attempting ...
Kuo-Hao Chang, L. Jeff Hong, Hong Wan
UAI
2000
13 years 8 months ago
Fast Planning in Stochastic Games
Stochastic games generalize Markov decision processes MDPs to a multiagent setting by allowing the state transitions to depend jointly on all player actions, and having rewards de...
Michael J. Kearns, Yishay Mansour, Satinder P. Sin...
ATAL
2010
Springer
13 years 8 months ago
Self-organization for coordinating decentralized reinforcement learning
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah
CORR
2010
Springer
127views Education» more  CORR 2010»
13 years 7 months ago
Mean field for Markov Decision Processes: from Discrete to Continuous Optimization
We study the convergence of Markov Decision Processes made of a large number of objects to optimization problems on ordinary differential equations (ODE). We show that the optimal...
Nicolas Gast, Bruno Gaujal, Jean-Yves Le Boudec