DRS automatically selects decision-relevant concepts from candidates for RL agents, supplies performance bounds, recovers manual sets, and improves test-time interventions on benchmarks and healthcare tasks.
Each feature corresponds to a scalar quantity, such as an absolute level, rate of change, or control signal, and no tem- poral differencing is applied
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Selecting Decision-Relevant Concepts in Reinforcement Learning
DRS automatically selects decision-relevant concepts from candidates for RL agents, supplies performance bounds, recovers manual sets, and improves test-time interventions on benchmarks and healthcare tasks.