An Evolutionary Approach to Find Optimal Policies with an Agent-Based Simulation

Autor: de Bufala, Nicolas, Kant, Jean-Daniel

Publikováno v: Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems(AAMAS 2019)
18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019)
18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), May 2019, Montreal, Canada

International audience; In this paper, we introduce a new agent-based method to build a decision-aid tool aimed to improve policy design. In our approach, a policy is defined as a set of levers, modelling the set of actions, the means to impact a com

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::b40b6a95e9b7248721bb14ce1b578fbf
https://hal.archives-ouvertes.fr/hal-02305399/document