Value Function Based Production Scheduling
Production scheduling in which we account for a probability distribution on future jobs by means of kernel-based value function approximation
Q2: Memory-based active learning for optimizing noisy continuous functions
Maximizing a very noisy function in k-dimensional space with few samples
Learning Evaluation Functions for Global Optimization and Boolean Satisfiability
Using Prediction to Improve Combinatorial Optimization Search
Automatically improving combinatorial search by reinforcement-learning-style analysis of earlier runs
Algorithms for Approximating Optimal Value Functions in Acyclic Domains
Using "Rollouts" to make value-function-based RL more practical
Generalization in Reinforcement Learning: Safely Approximating the Value Function
An introduction to the ways that naive application of function approximation of value functions can fail.
Proceedings of the Workshop on Value Function Approximation, Machine Learning Conference 1995.
Short talks from a workshop about value function approximation