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Jan 7, 2022 · Abstract: Reinforcement learning is one of the algorithms used in multi-agent systems to promote agent cooperation.
The Low-level strategy, Group Cooperation Network (GCoNet), is a method of centralized training and centralized execution within a group, which effectively ...
The Naive Bayes classifier is applied to predict the actions of other agents. Moreover, the sharing-policy mechanism is introduced into multi-agent ...
Oct 14, 2023 · Developing effective multi-agent systems (MASs) is critical for many applications requiring collaboration and coordination with humans.
Jan 31, 2022 · In this work, we shed light on the theoretical underpinnings of CG for cooperative multi-agent systems (MAS).
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Our aim is to help enable RL research for the class of applications that involve multiple teams of agents where each team may have unique learning strategies ...
Feb 1, 2023 · This paper introduces the concept of grouping into multi-agent reinforcement learning (MARL) and provides a novel formulation of Group-oriented MARL (GoMARL).
Dec 4, 2019 · This video provides a high-level illustration of our approach to multi-agent cooperation, including how we use task assignment to win battles in ...
Jun 20, 2023 · Abstract:In cooperative Multi-Agent Reinforcement Learning (MARL) agents are required to learn behaviours as a team to achieve a common goal.
Nov 29, 2024 · This paper introduces a novel approach to enhance the stability and efficiency of R-STDP in the context of federated learning.