Computational Model Library

PredPreyGrass (1.0.0)

Exploring learned cooperation, coevolution and free-riding. Learning is achieved through Multi-Agent Deep Reinforcement Learning (MADRL) in an ecological environment. The environment emits no other than sparse reproduction rewards. No reward shaping, no explicit cooperation signal.

cooperative_hunting_10MB.gif

Release Notes

First release

Associated Publications

PredPreyGrass 1.0.0

Submitted by HBP1969 Published May 17, 2026 Last modified May 17, 2026
multi-agent reinforcement learning deep reinforcement learning coevolution cooperation social dilemma reinforcement learning

Exploring learned cooperation, coevolution and free-riding. Learning is achieved through Multi-Agent Deep Reinforcement Learning (MADRL) in an ecological environment. The environment emits no other than sparse reproduction rewards. No reward shaping, no explicit cooperation signal.

Release Notes

First release

Cite this Model

HBP1969 (2026, May 17). “PredPreyGrass” (Version 1.0.0). CoMSES Computational Model Library. Retrieved from: https://www.comses.net/codebases/0c362544-c7cf-4498-b7d7-6ef8f6be5960/releases/1.0.0/

References

RLlib: Industry-Grade, Scalable Reinforcement Learning
Paper Collection of Multi-Agent Reinforcement Learning (MARL)
Multi-Agent Reinforcement Learning: Foundations and Modern Approaches. Stefano V. Albrecht, Filippos Christianos, and Lukas Schäfer

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Contributors
HBP1969
External Repository
github.com/doesburg11/PredPreyGrass
DOI
No assigned DOI
Model Version
1.0.0
License
MIT
Programming Language
Python 3.11.11
Software Framework
Ray
Operating System
Unix/Linux
Publish Date
Sunday, May 17, 2026
Last Updated
Sunday, May 17, 2026
Downloads 0
Peer Review
Unreviewed
Version Submitter First published Last modified Status
1.0.0 HBP1969 Sun May 17 10:58:04 2026 Sun May 17 10:58:07 2026 Published

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