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When Do Options Help? Policy Necrosis and Redundant Coverage in Option-Critic
Not provided
reinforcement learningoption-criticpolicy exploration
2609.05508
Builder Relevance
1h ago60%
Abstract
The paper discusses the limitations of the option-critic framework in reinforcement learning, particularly focusing on policy necrosis and the effects of redundant options.
Reality Card
Core Claim
The study reveals that adding more options does not improve performance due to issues like policy necrosis and ineffective termination rules.
Method / Result
The chance of all options failing in the same state drops from 59% to 4% with additional options.
Limitations
The termination rule learned by option-critic contributes nothing to performance, leading to potential exploration issues.
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