Yamada, J;
Shawe-Taylor, J;
Fountas, Z;
(2020)
Evolution of a Complex Predator-Prey Ecosystem on Large-scale Multi-Agent Deep Reinforcement Learning.
In:
Proceedings of the 2020 International Joint Conference on Neural Networks (IJCNN).
IEEE: Glasgow, UK.
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Abstract
Simulation of population dynamics is a central research theme in computational biology, which contributes to understanding the interactions between predators and preys. Conventional mathematical tools of this theme, however, are incapable of accounting for several important attributes of such systems, such as the intelligent and adaptive behavior exhibited by individual agents. This unrealistic setting is often insufficient to simulate properties of population dynamics found in the real-world. In this work, we leverage multi-agent deep reinforcement learning, and we propose a new model of large-scale predator-prey ecosystems. Using different variants of our proposed environment, we show that multi-agent simulations can exhibit key real-world dynamical properties. To obtain this behavior, we firstly define a mating mechanism such that existing agents reproduce new individuals bound by the conditions of the environment. Furthermore, we incorporate a real-time evolutionary algorithm and show that reinforcement learning enhances the evolution of the agents' physical properties such as speed, attack and resilience against attacks.
| Type: | Proceedings paper |
|---|---|
| Title: | Evolution of a Complex Predator-Prey Ecosystem on Large-scale Multi-Agent Deep Reinforcement Learning |
| Event: | 2020 International Joint Conference on Neural Networks (IJCNN) |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/IJCNN48605.2020.9206765 |
| Publisher version: | https://doi.org/10.1109/IJCNN48605.2020.9206765 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10117582 |
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