Multi-Agent Pursuit-Evasion Game Based on Organizational Architecture
No Thumbnail Available
Date
2019-03-01
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Multi-agent coordination mechanisms are frequently used in pursuit-evasion games with the aim of
enabling the coalitions of the pursuers and unifying
their individual skills to deal with the complex tasks
encountered. In this paper, we propose a coalition formation algorithm based on organizational principles
and applied to the pursuit-evasion problem. In order to
allow the alliances of the pursuers in different pursuit
groups, we have used the concepts forming an organizational modeling framework known as YAMAM (Yet
Another Multi Agent Model). Specifically, we have
used the concepts Agent, Role, Task, and Skill, proposed in this model to develop a coalition formation
algorithm to allow the optimal task sharing. To control
the pursuers' path planning in the environment as well
as their internal development during the pursuit, we
have used a Reinforcement learning method (Q-learning). Computer simulations reflect the impact of the
proposed techniques.
ACM CCS (2012) Classification: Computing methodologies → Artificial intelligence → Distributed artificial intelligence → Multi-agent systems
Theory of computation → Theory and algorithms for
application domains → Algorithmic game theory and
mechanism design → Convergence and learning in
games