Article

CAUSAL EXPLAINABLE REINFORCEMENT LEARNING FOR RELIABLE AUTONOMOUS DECISION-MAKING IN DYNAMIC ENVIRONMENTS

2026-02-27

Abstract excerpt

Autonomous systems require three essential decision-making capabilities which must be both dependable and able to adjust their operation while providing users with system status information. Traditional Reinforcement Learning (RL) methods depend on learning that uses correlation data yet these methods cannot discover genuine cause-and-effect links which causes their performance to diminish during environmental shi...

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Literature Corpus work: 26f7277e-024e-5106-9ebe-14ed2e70c6a0
DOI: 10.22541/au.177222619.97704177/v1

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