Learning to incentivize other learning agents
Nettetmaximized by, other agents. Empirical research shows that augmenting an agent’s action space with a “give-reward” action can improve cooperation during certain training … NettetLearning to Incentivize Other Learning Agents. intrinsic reward comes from other agents (has individual env reward) not budget balance gradient update individual policy update intrinsic (incentive) reward: maximize individual env reward: (not budget balance) the same as LIIR; Learning to Share in Multi-Agent Reinforcement Learning
Learning to incentivize other learning agents
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NettetEach agent learns its own incentive function by explicitly accounting for its impact on the learning of recipients and, through them, the impact on its own extrinsic objective. We … Nettet1. jan. 2024 · PDF On Jan 1, 2024, Kyrill Schmid and others published Learning to Penalize Other Learning Agents ... Learning to incentivize other learning agents. arXiv preprint arXiv:2006.06051.
NettetCooperative multi-agent learning: The state of the art. Autonomous agents and multi-agent systems, Vol. 11, 3 (2005), 387--434. ... Jiachen Yang, Ang Li, Mehrdad Farajtabar, Peter Sunehag, Edward Hughes, and Hongyuan Zha. 2024. Learning to Incentivize Other Learning Agents. Advances in Neural Information Processing Systems, Vol. 33 … NettetEach agent learns its own incentive function by explicitly accounting for its impact on the learning of recipients and, through them, the impact on its own extrinsic objective. We demonstrate in experiments that such agents significantly outperform standard RL and opponent-shaping agents in challenging general-sum Markov games, often by finding …
NettetThe challenge of developing powerful and general Reinforcement Learning (RL) agents has received increasing attention in recent years. Much of this effort has focused on the single-agent setting, in which an agent maxi… Nettet10. jun. 2024 · Request PDF Learning to Incentivize Other Learning Agents The challenge of developing powerful and general Reinforcement Learning (RL) agents …
NettetTranslated to the framework of Markov games for multi-agent reinforcement learning (MARL) [26], the key insight is to remove the constraints of an immutable reward …
Nettet28. feb. 2024 · How do you incentivize self-interested agents to $\\textit{explore}$ when they prefer to $\\textit{exploit}$? We consider complex exploration problems, where … the torii currency solutionNettetan agent that learns an incentive function to reward other learning agents by explicitly accounting for the impact of given incentives on its own performance, through the … setworks softwareNettetLearning to Incentivize Other Learning Agents Meta Review The reviewers are in consensus that this paper provides a useful new framework for sharing rewards in multi … set work schedule in teamsNettet16. des. 2024 · Learning to incentivize other learning agents. In NeurIPS, 2024. Qatten: A general framework for cooperative multiagent reinforcement learning. Jan 2024; Yaodong Yang; Jianye Hao; Ben Liao; set worksheet as active sheetNettetLearning to Incentivize Other Learning Agents. Advances in Neural Information Processing Systems, Vol. 33 (2024). Google Scholar; Y Yang, R Luo, M Li, M Zhou, W Zhang, and J Wang. 2024. Mean Field Multi-Agent Reinforcement Learning. In 35th International Conference on Machine Learning, ICML 2024, Vol. 80. the torii gates mark a transition fromNettetLearning to Incentivize Others. This is the code for experiments in the paper Learning to Incentivize Other Learning Agents. Baselines are included. Setup. Python 3.6; … set workspace folder vscodeNettetThe new learning problem for an agent becomes two-fold: learn a policy that optimizes the total extrinsic rewards and incentives it receives, and learn an incentive … set working location in outlook