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A Genetic Algorithm-Oriented Model of Agent Persuasion for Multi-agent System Negotiation

  • Samantha JiménezEmail author
  • Víctor H. Castillo
  • Bogart Yail Márquez
  • Arnulfo Alanis
  • Leonel Soriano-Equigua
  • José Luis Álvarez-Flores
Conference paper
  • 22 Downloads
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 186)

Abstract

In recent years, reaching agreements is an important problem in multi-agent systems (MAS), which require different types of dialogues between agents. Persuasion is one of them and it is traditionally based on first order logic. However, this type of technique is not adequate for solving complex problems. This situation requires developing new models for optimizing an agent persuasion process. This work presents a persuasion model for MAS based in genetic algorithms (GA) for reaching agreements in problem solving. The objective of this work is to optimize the negotiation between agents that solve complex problems. First, it was designed the persuasion model. Then, it was implemented and evaluated in experimental scenarios and it was compared its results against traditional models. The experimental results showed that a GA-oriented persuasion model optimizes the negotiation in MAS by improving execution time, which also eventually will optimize the processes carried out by MAS.

Keywords

Multi-agent system Genetic algorithm Persuasion Negotiation 

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Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Samantha Jiménez
    • 1
    Email author
  • Víctor H. Castillo
    • 2
  • Bogart Yail Márquez
    • 1
  • Arnulfo Alanis
    • 1
  • Leonel Soriano-Equigua
    • 2
  • José Luis Álvarez-Flores
    • 2
  1. 1.Instituto Tecnológico de TijuanaTijuanaMexico
  2. 2.Universidad de ColimaColimaMexico

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