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GECCO
2007
Springer
235views Optimization» more  GECCO 2007»
14 years 4 months ago
Expensive optimization, uncertain environment: an EA-based solution
Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function e...
Maumita Bhattacharya
GECCO
2007
Springer
186views Optimization» more  GECCO 2007»
14 years 4 months ago
ICSPEA: evolutionary five-axis milling path optimisation
ICSPEA is a novel multi-objective evolutionary algorithm which integrates aspects from the powerful variation operators of the Covariance Matrix Adaptation Evolution Strategy (CMA...
Jörn Mehnen, Rajkumar Roy, Petra Kersting, To...
JAIR
2002
163views more  JAIR 2002»
13 years 9 months ago
Efficient Reinforcement Learning Using Recursive Least-Squares Methods
The recursive least-squares (RLS) algorithm is one of the most well-known algorithms used in adaptive filtering, system identification and adaptive control. Its popularity is main...
Xin Xu, Hangen He, Dewen Hu
AAAI
1998
13 years 11 months ago
Applying Online Search Techniques to Continuous-State Reinforcement Learning
In this paper, we describe methods for e ciently computing better solutions to control problems in continuous state spaces. We provide algorithms that exploit online search to boo...
Scott Davies, Andrew Y. Ng, Andrew W. Moore
ATAL
2008
Springer
14 years 4 days ago
Sigma point policy iteration
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...