qplex (SMAC Corp)
90
Structured Review
SMAC Corp
qplex
Qplex, supplied by SMAC Corp, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/qplex/qplex/pm38901092-174-15-43
Average 90 stars, based on 1 article reviews
Qplex, supplied by SMAC Corp, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/qplex/qplex/pm38901092-174-15-43
Average 90 stars, based on 1 article reviews
qplex - by Bioz Stars,
2026-10
90/100 stars
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Related Articles
other:Article Title: QFuture: Learning Future Expectation Cognition in Multi-Agent Reinforcement Learning Article Snippet: In multi-agent reinforcement learning (MARL), agents must learn to cooperate by observing the environment and selecting actions that maximize their rewards.. However, this learning process can be hampered by myopia, wherein agents’ strategies fail to consider the long-term consequences of their actions.. A primary reason for this problem is the inaccurate estimation of the long-term value of each action. Article Title: HyperComm: Hypergraph-based communication in multi-agent reinforcement learning. Article Snippet: In the realm of fully cooperative multi-agent reinforcement learning (MARL), effective communication can induce implicit cooperation among agents and improve overall performance.. In current communication strategies, agents are allowed to exchange local observations or latent embeddings, which can augment individual local policy inputs and mitigate uncertainty in local decision-making processes.. Unfortunately, in previous communication schemes, agents may potentially receive irrelevant information, which increases training difficulty and leads to poor performance in complex settings. |