Chain of command in autonomous cooperative agents for battles in real-time strategy games
Daylamani-Zad, Damon, Graham, Letitia B. and Paraskevopoulos, Ioannis (2018) Chain of command in autonomous cooperative agents for battles in real-time strategy games. Journal of Computers in Education, 6 (1). pp. 21-52. ISSN 2197-9987 (Print), 2197-9995 (Online) (doi:https://doi.org/10.1007/s40692-018-0119-8)
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21857 DAYLAMANI-ZAD Chain_of _Command_in_Autonomous_Cooperative_Agents_(OA)_2018.pdf - Published Version Available under License Creative Commons Attribution. Download (1MB) | Preview |
Abstract
This paper investigates incorporating chain of command in swarm intelligence of honey bees to create groups of ranked co-operative autonomous agents for an RTS game in to create and re-enact battle simulations. The behaviour of the agents are based on the foraging and defensive behaviours of honey bees, adapted to a human environment. The chain of command is implemented using a hierarchical decision model. The groups consist of multiple model-based reflex agents, with individual blackboards for working memory, with a colony level blackboard to mimic the foraging patterns and include commands received from ranking agents. An agent architecture and environment are proposed that allows for creation of autonomous cooperative agents. The behaviour of agents is then evaluated both mathematically and empirically using an adaptation of anytime universal intelligence test and agent believability metric.
Item Type: | Article |
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Additional Information: | © The Author(s) 2018. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
Uncontrolled Keywords: | Real-time strategy games, Swarm intelligence, Agent architecture, Multi-agent intelligence, Artificial intelligence, Chain of command |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Faculty / School / Research Centre / Research Group: | Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science |
Last Modified: | 04 Mar 2022 13:06 |
URI: | http://gala.gre.ac.uk/id/eprint/21857 |
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