Multi-agent learning problems can in principle be solved by treating the joint actions of the agents as single actions and applying single-agent Q-learning.
Abstract- More and more Artificial Intelligence researchers focused on the reinforcement learning(RL)-based multi-agent system(MAS). Multi-agent learning ...
... 2) Multi-Agent Q-Learning (MQL) Algorithm: In the MQL, each UAV takes account of other UAVs' flight decisions with the objective of promoting cooperative ...
More and more Artificial Intelligence researchers focused on the reinforcement learning (RL)-based multi-agent system (MAS). Multi-agent learning problems ...
Jan 10, 2024 · Cooperative multi-agent reinforcement learning is a powerful tool to solve many real-world cooperative tasks, but restrictions of real-world ...
Nov 9, 2021 · In this paper, we formalize a multi-agent fitted Q-iteration framework for analyzing factorized multi-agent Q-learning. Based on this framework, ...
Nov 30, 2023 · This paper constructs a multi-agent massive target cooperative search mission planning model and proposes an improved reinforcement learning algorithm
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In this paper, we formalize a multi- agent fitted Q-iteration framework for analyzing factorized multi-agent Q-learning. Based on this framework, we investigate ...
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This study introduces a novel approach to data gathering in energy-harvesting wireless sensor networks (EH-WSNs) utilizing cooperative multi-agent ...
Jul 3, 2024 · Mixed setting - Agents have varying goals. In a cooperative setting, all agents share aligning goals, where the reward function is typically.