Generating inspiration for agent design by reinforcement learning
Information and Software Technology
PROGRAMMING AGENT BEHAVIOR BY LEARNING IN SIMULATION MODELS
Applied Artificial Intelligence - Eighth European Workshop on Multi-Agent Systems EUMAS 2010
How to design agent-based simulation models using agent learning
Proceedings of the Winter Simulation Conference
| Hi-index | 0.00 |
The process of finding the appropriate agent behavior is a cumbersome task -- no matter whether it is for agent-based software or simulation models. Machine Learning can help by generating partial or preliminary versions of the agent low-level behavior. However, for actually being useful for the human modeler the results should be interpretable, which may require some post-processing step after the actual behavior learning. In this contribution we test the sensitivity of the resulting, interpretable behavior program with respect to parameters and components of the function that describes the intended behavior.