Constrained Markov Decision Processes with Expected Total Reward Criteria
PulseAugur coverage of Constrained Markov Decision Processes with Expected Total Reward Criteria — every cluster mentioning Constrained Markov Decision Processes with Expected Total Reward Criteria across labs, papers, and developer communities, ranked by signal.
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New RL algorithm MO-IKE enhances LLM knowledge editing
Researchers have developed a new multi-objective reinforcement learning algorithm called MO-IKE to improve in-context knowledge editing for large language models. This method addresses limitations in previous approaches…
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AI framework enhances IT remediation safety with risk-based decisions
Researchers have developed a new framework for automated remediation in IT operations, framing it as a risk-constrained intervention decision problem. This approach utilizes Constrained Markov Decision Processes (CMDPs)…
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New CMDP algorithm bypasses Slater's condition for improved performance
Researchers have developed a new algorithm for online episodic Constrained Markov Decision Processes (CMDPs) that improves upon existing methods. This algorithm handles both stochastic and adversarial constraints withou…