Decision support systems (DSS) increasingly combine data, models, rules, workflows, and agentic tool use, but they still offer limited support for establishing the defensibility of decision outputs: framing the problem, qualifying evidence, bounding claims, generating options, comparing alternatives, and learning from...
Federated reinforcement learning (FedRL) permits agents to optimize a shared policy without exchanging raw trajectories, but noisy policy-gradient estimates make malicious updates difficult to distinguish from honest variation. We propose FedPG-BR, which couples stochastic variance-reduced policy gradient (SVRPG) updat...
Wen-Yuan Tian, Jing-Xuan Zhou, Miao Yu et al.· 2026 12th International Conf...· 0 citations
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