An introduction to genetic algorithms
An introduction to genetic algorithms
Understanding agent systems
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Multi-Agent Systems: An Introduction to Distributed Artificial Intelligence
Know thine enemy: a champion robocup coach agent
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Using response probability to build system redundancy in multiagent systems
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
| Hi-index | 12.05 |
This paper describes a new model to automatically generating dynamic formation strategies for robotic soccer applications based on game conditions, regarded to as favorable or unfavorable for a robotic team. Decisions are distributedly computed by the players of a multi-agent team. A game policy is defined and applied by a human coach who establishes the attitude of the team for defending or attacking. A simple neural net model is applied using current and previous game experience to classify the game's parameters so that the new game conditions can be determined so that a robotic team can modify its strategy on-the-fly. Experiments and results of the proposed model for a robotic soccer team show the promise of the approach.