A process algebra with guarded choice and recursion is compiled to global and then projected local Mealy machines that filter safe joint actions for each agent in Dec-POMDPs using belief-style state subsets.
Safe multi-agent reinforcement learning via shielding,
2 Pith papers cite this work. Polarity classification is still indexing.
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A literature review of safe RL using Lyapunov and barrier functions that identifies a shift to model-free methods since 2017, well-defined open problems per approach class, and high-dimensional scalability as the main barrier.
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Generating Local Shields for Decentralised Partially Observable Markov Decision Processes
A process algebra with guarded choice and recursion is compiled to global and then projected local Mealy machines that filter safe joint actions for each agent in Dec-POMDPs using belief-style state subsets.
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A Review On Safe Reinforcement Learning Using Lyapunov and Barrier Functions
A literature review of safe RL using Lyapunov and barrier functions that identifies a shift to model-free methods since 2017, well-defined open problems per approach class, and high-dimensional scalability as the main barrier.