Behavior modeling from learning agents: sensitivity to objective function details
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
How to design agent-based simulation models using agent learning
Proceedings of the Winter Simulation Conference
Behavior Abstraction Robustness in Agent Modeling
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Learning agent models in SeSAm
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
| Hi-index | 0.00 |
A candidate-learning architecture is the combination of reinforcement learning and decision tree learning. The former generates a policy for agent behavior and the latter is used for abstraction and interpretation purposes. Here, we focus on the relation between policy-learning convergence and the quality of the abstracted model produced from that.