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2
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Learning Evaluation Functions
– Justin A. Boyan, Scott E. Fahlman, Tom Mitchell
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49
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Learning Evaluation Functions to Improve Optimization by Local Search
– Justin Boyan, Andrew W. Moore, Pack Kaelbling
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56
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Learning Evaluation Functions for Global Optimization and Boolean Satisfiability
– Justin A. Boyan, Andrew W. Moore
- 1998
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Learning Evaluation Functions to Improve Local Search
– Justin A. Boyan, Andrew W. Moore
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16
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Value Function Based Production Scheduling
– Jeff G. Schneider, Justin A. Boyan, Andrew W. Moore
- 1998
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1
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A Study on Architecture, Algorithms, and Applications of Approximate Dynamic Programming Based Approach to Optimal Control
– Jong Min Lee
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13
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Solving Combinatorial Optimization Tasks by Reinforcement Learning: A General Methodology Applied to Resource-Constrained Scheduling
– Wei Zhang, Thomas G. Dietterich
- 1998
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31
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Hierarchical Learning with Procedural Abstraction Mechanisms
– Justinian Rosca
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1
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Learning as Applied to Simulated Annealing
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20
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Simulated Annealing with Extended Neighbourhood
– Xin Yao
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Learning as Applied to Stochastic Optimization for Standard Cell Placement
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36
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Optimal design of a CMOS op-amp via geometric programming
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17
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Memetic Algorithms for the Traveling Salesman Problem
– Peter Merz, Bernd Freisleben
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61
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A Genetic Local Search Algorithm for Solving Symmetric and Asymmetric Traveling Salesman Problems
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48
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New Genetic Local Search Operators for the Traveling Salesman Problem
– Bernd Freisleben, Peter Merz
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Dynamic Optimization for Optimal Control of Water Distribution Systems
– Emre Ertin, Anthony N. Dean, Mathew L. Moore, Kevin L. Priddy
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Economics of Distributed Web Search: A Machine Learning Approach
– Rinat Khoussainov
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Multi-Agent Reinforcement Learning with Vicarious Rewards
– Kevin Irwig, Wayne Wobcke, Martlesham Heath, Ipswich Ip Re
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Robust Value Function Approximation by Working Backwards
– Justin A. Boyan, Andrew W. Moore
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