loading
Papers

Research.Publish.Connect.

Paper

Authors: B. K. Swathi Prasad ; Aditya G. Manjunath and Hariharan Ramasangu

Affiliation: M. S. Ramaiah University of Applied Sciences, India

ISBN: 978-989-758-219-6

Keyword(s): Formation, Pattern, Q-learning, Algorithm, Episode.

Related Ontology Subjects/Areas/Topics: Agents ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Bioinformatics ; Biomedical Engineering ; Distributed and Mobile Software Systems ; Enterprise Information Systems ; Information Systems Analysis and Specification ; Knowledge Engineering and Ontology Development ; Knowledge-Based Systems ; Methodologies and Technologies ; Multi-Agent Systems ; Operational Research ; Physical Agents ; Simulation ; Software Engineering ; State Space Search ; Symbolic Systems

Abstract: This work provides details a simulation experiment and analysis of Q-learning applied to multi-agent systems. Six agents interact within the environment to form hexagon, square and triangle, by reaching their specific goal states. In the proposed approach, the agents form a hexagon and the maximum dimension of this pattern is be reduced to form patterns with smaller dimensions. A decentralised approach of controlling the agents via Q-Learning was adopted which reduced complexity. The agents will be able to either move forward, backward and sideways based on the decision taken. Finally, the Q-Learning action-reward system was designed such that the agents could exploit the system which meant that they would earn high rewards for correct actions and negative rewards so the opposite.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.210.22.132

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Prasad, B.; Manjunath, A. and Ramasangu, H. (2017). Multi-agent Polygon Formation using Reinforcement Learning.In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-758-219-6, pages 159-165. DOI: 10.5220/0006187001590165

@conference{icaart17,
author={B. K. Swathi Prasad. and Aditya G. Manjunath. and Hariharan Ramasangu.},
title={Multi-agent Polygon Formation using Reinforcement Learning},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2017},
pages={159-165},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006187001590165},
isbn={978-989-758-219-6},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - Multi-agent Polygon Formation using Reinforcement Learning
SN - 978-989-758-219-6
AU - Prasad, B.
AU - Manjunath, A.
AU - Ramasangu, H.
PY - 2017
SP - 159
EP - 165
DO - 10.5220/0006187001590165

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.