Event-Triggered and Time-Triggered Duration Calculus for Model-Free Reinforcement Learning

Kalyani Dole,Ashutosh Gupta,John Komp,Shankaranarayanan Krishna,Ashutosh Trivedi

2021 IEEE Real-Time Systems Symposium (RTSS)（2021）

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摘要

Reinforcement Learning (RL) is a sampling based approach to optimization, where learning agents rely on scalar reward signals to discover optimal solutions. The specification of learning objectives as scalar rewards is tedious and error prone, and more so for real-time systems with complex time-critical requirements. This paper advocates the use of Duration Calculus (DC)—a highly expressive real-t...

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关键词

Learning automata,Computational modeling,Stochastic processes,Pacemakers,Reinforcement learning,Probabilistic logic,Real-time systems

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