@article{M9BC3A5FA,
title = "Reinforcement Learning with the Law of Diminishing Marginal Utility: Efficient and Equitable Resource Allocation in Multi-Agent Systems",
journal = "Journal of KIISE, JOK",
year = "2025",
issn = "2383-630X",
doi = "10.5626/JOK.2025.52.5.374",
author = "Yunsu Lee, Byoung-Tak Zhang",
keywords = "MARL, game theory, law of diminishing marginal utility, pareto optima",
abstract = "The law of diminishing marginal utility is an economic theory stating that as additional units of a good are consumed, the utility gained from each additional unit is decreased. We incorporated the law of diminishing marginal utility into multi-agent reinforcement learning for resource allocation, demonstrating that optimal distribution could emerge without direct communication among agents. This approach aligns with market principles, where individual self-Ainterested actions can lead to maximization of total utility. Experimental results in a grid-world environment showed that when two agents competed for two resources, applying the law of diminishing marginal utility led to a more equitable and Pareto-optimal allocation of resources."
}