Proceedings of the fifth international conference on Autonomous agents
Introduction to Reinforcement Learning
Introduction to Reinforcement Learning
Using Optimal Foraging Models to Evaluate Learned Robotic Foraging Behavior
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Foraging Theory for Autonomous Vehicle Decision-making System Design
Journal of Intelligent and Robotic Systems
Towards Energy Optimization: Emergent Task Allocation in a Swarm of Foraging Robots
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Multi-armed bandit algorithms and empirical evaluation
ECML'05 Proceedings of the 16th European conference on Machine Learning
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We investigate the problem of a robot maximizing its long-term average rate of return on work. We present a means to obtain an estimate of the instantaneous rate of return when work is rewarded in discrete atoms, and a method that uses this to recursively maximize the long-term average return when work is available in localized patches, each with locally diminishing returns. We examine a puck-foraging scenario, and test our method in simulation under a variety of conditions. However, the analysis and approach applies to the general case.