Simulating Dynamic Ecosystems with Co-Evolutionary Agents

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard Standard

Simulating Dynamic Ecosystems with Co-Evolutionary Agents. / Fergusson, Gary; Vidal, Franck.

Proceedings of Computer Graphics & Visual Computing Conference 2020 (CGVC 2020). The Eurographics Association, 2020.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

HarvardHarvard

Fergusson, G & Vidal, F 2020, Simulating Dynamic Ecosystems with Co-Evolutionary Agents. in Proceedings of Computer Graphics & Visual Computing Conference 2020 (CGVC 2020). The Eurographics Association. https://doi.org/10.2312/cgvc.20201148

APA

Fergusson, G., & Vidal, F. (2020). Simulating Dynamic Ecosystems with Co-Evolutionary Agents. In Proceedings of Computer Graphics & Visual Computing Conference 2020 (CGVC 2020) The Eurographics Association. https://doi.org/10.2312/cgvc.20201148

CBE

Fergusson G, Vidal F. 2020. Simulating Dynamic Ecosystems with Co-Evolutionary Agents. In Proceedings of Computer Graphics & Visual Computing Conference 2020 (CGVC 2020). The Eurographics Association. https://doi.org/10.2312/cgvc.20201148

MLA

Fergusson, Gary and Franck Vidal "Simulating Dynamic Ecosystems with Co-Evolutionary Agents". Proceedings of Computer Graphics & Visual Computing Conference 2020 (CGVC 2020). The Eurographics Association. 2020. https://doi.org/10.2312/cgvc.20201148

VancouverVancouver

Fergusson G, Vidal F. Simulating Dynamic Ecosystems with Co-Evolutionary Agents. In Proceedings of Computer Graphics & Visual Computing Conference 2020 (CGVC 2020). The Eurographics Association. 2020 https://doi.org/10.2312/cgvc.20201148

Author

Fergusson, Gary ; Vidal, Franck. / Simulating Dynamic Ecosystems with Co-Evolutionary Agents. Proceedings of Computer Graphics & Visual Computing Conference 2020 (CGVC 2020). The Eurographics Association, 2020.

RIS

TY - GEN

T1 - Simulating Dynamic Ecosystems with Co-Evolutionary Agents

AU - Fergusson, Gary

AU - Vidal, Franck

PY - 2020

Y1 - 2020

N2 - As video games grow in complexity and require increasingly large and immersive environments, there is a need for more believable and dynamic characters not controlled by the player, known as non-player character (NPC). Video game developers will often face the challenge of designing these NPCs in a time efficient manner. We propose an agent-based Cooperative Co-evolution Algorithm (CCEA) where NPCs are implemented as artificial life (AL) agents that are created through an evolutionary process based on simple rules. The virtual environment can be filled with a range of interesting agents, each acting independently from one another, to fulfil their own wants and needs. The proposed middleware framework is suitable for computer animation of NPCs and the development of video games, especially where swarm intelligence is simulated. We proved that agents implemented with a very limited number of variables making up their genome can be successfully integrated in a co-evolutionary multi-agent system (CoEMAS). Results showed promising levels of speciation and interesting emergent and plausible behaviours amongst the agents.

AB - As video games grow in complexity and require increasingly large and immersive environments, there is a need for more believable and dynamic characters not controlled by the player, known as non-player character (NPC). Video game developers will often face the challenge of designing these NPCs in a time efficient manner. We propose an agent-based Cooperative Co-evolution Algorithm (CCEA) where NPCs are implemented as artificial life (AL) agents that are created through an evolutionary process based on simple rules. The virtual environment can be filled with a range of interesting agents, each acting independently from one another, to fulfil their own wants and needs. The proposed middleware framework is suitable for computer animation of NPCs and the development of video games, especially where swarm intelligence is simulated. We proved that agents implemented with a very limited number of variables making up their genome can be successfully integrated in a co-evolutionary multi-agent system (CoEMAS). Results showed promising levels of speciation and interesting emergent and plausible behaviours amongst the agents.

U2 - https://doi.org/10.2312/cgvc.20201148

DO - https://doi.org/10.2312/cgvc.20201148

M3 - Conference contribution

BT - Proceedings of Computer Graphics & Visual Computing Conference 2020 (CGVC 2020)

PB - The Eurographics Association

ER -