Bellman operator
PulseAugur coverage of Bellman operator — every cluster mentioning Bellman operator across labs, papers, and developer communities, ranked by signal.
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New CCPL method tackles delayed consequences in reinforcement learning
Researchers have developed a new approach called Causal Consequence-Penalized Learning (CCPL) to address limitations in constrained reinforcement learning (RL) where consequences are delayed and stochastic. CCPL introdu…
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New CVaR MDP formulation enhances risk-sensitive policy learning
Researchers have developed a novel formulation for static Conditional Value-at-Risk (CVaR) objectives in Markov Decision Processes (MDPs) to better handle tail-end risks in safety-critical applications. Their approach i…
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New framework tackles model mismatches in multi-agent reinforcement learning
Researchers have developed a new framework for stationary robust mean-field games to address challenges in deploying multi-agent reinforcement learning (MARL) in real-world scenarios. The framework tackles model mismatc…