Online Learning of Temporal Dependencies for Sustainable Foraging Problem
<|reference_start|>Online Learning of Temporal Dependencies for Sustainable Foraging Problem: The sustainable foraging problem is a dynamic environment testbed for exploring the forms of agent cognition in dealing with social dilemmas in a multi-agent setting. The agents need to resist the temptation of individual rewards through foraging and choose the collective long-term goal of sustainability. We investigate methods of online learning in Neuro-Evolution and Deep Recurrent Q-Networks to enable agents to attempt the problem one-shot as is often required by wicked social problems. We further explore if learning temporal dependencies with Long Short-Term Memory may be able to aid the agents in developing sustainable foraging strategies in the long term. It was found that the integration of Long Short-Term Memory assisted agents in developing sustainable strategies for a single agent, however failed to assist agents in managing the social dilemma that arises in the multi-agent scenario.<|reference_end|>
@article{payne2024online,
    title={Online Learning of Temporal Dependencies for Sustainable Foraging
  Problem},
    author={John Payne, Aishwaryaprajna, Peter R. Lewis},
    journal={arXiv preprint arXiv:2407.01501},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.01501},
    primaryClass={cs.MA cs.LG cs.NE}
}