In this article, we propose a trust evaluation model in MARL to evaluate the trustworthiness of the target agent. The trust evaluation of the target agent is ...
In this article, we propose a trust evaluation model in MARL to evaluate the trustworthiness of the target agent. The trust evaluation of the target agent is ...
This work looks into incorporating the concept of trust in a multi agent environment, allowing agents to compute trust they have on each other. The proposed ...
We propose a model for trust dynamics based on a multi-agent RL algorithm. We corroborate some trust concepts developed in social sciences within a ...
May 30, 2024 · Learning-based agents should adopt a protocol that allows them to reach consensus despite having one or more unreliable agents in the sys- tem.
May 30, 2024 · Learning-based agents should adopt a protocol that allows them to reach consensus despite having one or more unreliable agents in the system.
A Survey on Trust Evaluation Based on Machine Learning. Article. Oct 2020 ... based Virtual OrganisationS) which models an agent's trust in an interaction partner ...
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This article outlines a novel actor–critic (AC) approach tailored to cooperative MARL problems in sparsely rewarded domains.
The primary aim of TEs is to acquire high levels of trust, of value for future interactions with TRs. Tran and Cohen (Tran and Cohen 2004) includes seller.
May 13, 2022 · One of the major paradigms in Multi-Agent Reinforcement Learn- ing is Centralized Training with Decentralized Execution (CTDE). [18, 47, 54], ...