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» Guiding Inference with Policy Search Reinforcement Learning
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AAAI
2006
15 years 1 months ago
Sample-Efficient Evolutionary Function Approximation for Reinforcement Learning
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Shimon Whiteson, Peter Stone
95
Voted
AI
1999
Springer
14 years 11 months ago
Learning Action Strategies for Planning Domains
There are many different approaches to solving planning problems, one of which is the use of domain specific control knowledge to help guide a domain independent search algorithm. ...
Roni Khardon
ESANN
2003
15 years 29 days ago
Improving iterative repair strategies for scheduling with the SVM
The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources’ availabilities in ...
Kai Gersmann, Barbara Hammer
IEEECIT
2010
IEEE
14 years 9 months ago
Learning Autonomic Security Reconfiguration Policies
Abstract--We explore the idea of applying machine learning techniques to automatically infer risk-adaptive policies to reconfigure a network security architecture when the context ...
Juan E. Tapiador, John A. Clark
GECCO
2008
Springer
182views Optimization» more  GECCO 2008»
15 years 20 days ago
Scaling ant colony optimization with hierarchical reinforcement learning partitioning
This paper merges hierarchical reinforcement learning (HRL) with ant colony optimization (ACO) to produce a HRL ACO algorithm capable of generating solutions for large domains. Th...
Erik J. Dries, Gilbert L. Peterson