Logic + Reinforcement Learning + Deep Learning: A Survey

Andreas Bueff, Vaishak Belle

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

Reinforcement learning has made significant strides in recent years, including in the development of Atari and Go-playing agents. It is now widely acknowledged that logical syntax adds considerable flexibility in both the modelling of domains as well as the interpretability of domains. In this survey paper, we cover the fundamentals of how logic, reinforcement learning, and deep learning can be unified, with some ideas for future work.
Original languageEnglish
Title of host publicationProceedings of the 15th International Conference on Agents and Artificial Intelligence, 2023
PublisherSCITEPRESS
Pages713-722
Number of pages10
Volume3
ISBN (Electronic)9789897586231
DOIs
Publication statusPublished - 22 Feb 2023
EventThe 15th International Conference on Agents and Artificial Intelligence, 2023 - Lisbon, Portugal
Duration: 22 Feb 202324 Feb 2023
Conference number: 15
https://icaart.scitevents.org/Home.aspx

Publication series

NameInternational Conference on Agents and Artificial Intelligence
PublisherSCITEPRESS
ISSN (Electronic)2184-433X

Conference

ConferenceThe 15th International Conference on Agents and Artificial Intelligence, 2023
Abbreviated titleICAART 2023
Country/TerritoryPortugal
CityLisbon
Period22/02/2324/02/23
Internet address

Keywords / Materials (for Non-textual outputs)

  • Logic-based reinforcement learning

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