RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction

Research article (Proceedings of the International Conference on Automated Planning and Scheduling, 2021) · cited 17× · AI/ML
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RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction

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RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction is a scholarly article[1].

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  • RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction's instance of is recorded as scholarly article[2].

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APA 4ort.xyz Knowledge Graph. (2026). RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction. Retrieved May 24, 2026, from https://4ort.xyz/entity/reprel-integrating-relational-planning-and-reinforcement-learning-for-effective-abstraction
MLA “RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/reprel-integrating-relational-planning-and-reinforcement-learning-for-effective-abstraction.
BibTeX @misc{4ortxyz_reprel-integrating-relational-planning-and-reinforcement-learning-for-effective-abstraction_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction}}, year = {2026}, url = {https://4ort.xyz/entity/reprel-integrating-relational-planning-and-reinforcement-learning-for-effective-abstraction}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction — https://4ort.xyz/entity/reprel-integrating-relational-planning-and-reinforcement-learning-for-effective-abstraction (retrieved 2026-05-24)

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