A better-response strategy for self-interested planning agents

Jaume Jordán, Alejandro Torreño, Mathijs de Weerdt, Eva Onaindia

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)
26 Downloads (Pure)


When self-interested agents plan individually, interactions that prevent them from executing their actions as planned may arise. In these coordination problems, game-theoretic planning can be used to enhance the agents’ strategic behavior considering the interactions as part of the agents’ utility. In this work, we define a general-sum game in which interactions such as conflicts and congestions are reflected in the agents’ utility. We propose a better-response planning strategy that guarantees convergence to an equilibrium joint plan by imposing a tax to agents involved in conflicts. We apply our approach to a real-world problem in which agents are Electric Autonomous Vehicles (EAVs). The EAVs intend to find a joint plan that ensures their individual goals are achievable in a transportation scenario where congestion and conflicting situations may arise. Although the task is computationally hard, as we theoretically prove, the experimental results show that our approach outperforms similar approaches in both performance and solution quality.

Original languageEnglish
Pages (from-to)1020-1040
Number of pages21
JournalApplied Intelligence: the international journal of artificial intelligence, neural networks, and complex problem-solving technologies
Issue number4
Publication statusPublished - 2018


  • Best-response
  • Better-response
  • Game theory
  • Nash equilibrium
  • Planning

Fingerprint Dive into the research topics of 'A better-response strategy for self-interested planning agents'. Together they form a unique fingerprint.

Cite this