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» Learning Multi-modal Control Programs
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ATAL
2007
Springer
14 years 1 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
GECCO
2008
Springer
182views Optimization» more  GECCO 2008»
13 years 8 months 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
ICDCSW
2008
IEEE
14 years 1 months ago
Automated Addition of Fault-Tolerance to SCR Toolset: A Case Study
Automated addition of fault-tolerance to existing programs is highly desirable, as it allows the designer to focus on the system behavior in the absence of faults and leave the fa...
Fuad Abujarad, Sandeep S. Kulkarni
CP
2000
Springer
13 years 11 months ago
Constraint-Based Agents: The ABC's of CBA's
The Constraint-Based Agent (CBA) framework is a set of tools for designing, simulating, building, verifying, optimizing, learning and debugging controllers for agents embedded in a...
Alan K. Mackworth
FLAIRS
2003
13 years 8 months ago
Cost-Based Policy Mapping for Imitation
Imitation represents a powerful approach for programming and autonomous learning in robot and computer systems. An important aspect of imitation is the mapping of observations to ...
Srichandan V. Gudla, Manfred Huber