Improving the Learning Efficiency of Robot Path Planning via Fuzzified Deep Reinforcement Learning

Al Mahmud, Suaib, Ibrahim, Azhar Mohd, Khan, Mazbahur Rahman, Baqalaql, Odai Saeed, De Wilde, Philippe (2025) Improving the Learning Efficiency of Robot Path Planning via Fuzzified Deep Reinforcement Learning. In: 2025 IEEE International Conference on Fuzzy Systems (FUZZ). . pp. 1-8. IEEE (doi:10.1109/FUZZ62266.2025.11197609) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:112900)

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Official URL: https://doi.org/10.1109/FUZZ62266.2025.11197609

Item Type:	Conference or workshop item (Paper)
DOI/Identification number:	10.1109/FUZZ62266.2025.11197609
Uncontrolled keywords:	Fuzzy logic; Training; Uncertainty; Navigation; Simulation; Knowledge representation; Deep reinforcement learning; Path planning; Mobile robots; Fuzzy systems; Robot Path Planning; DRL; Fuzzy Logic; ANFIS; Neuro-Symbolic,
Institutional Unit:	Schools > School of Natural Sciences > Biosciences
Former Institutional Unit:	There are no former institutional units.
Funders:	University of Kent (https://ror.org/00xkeyj56)
Depositing User:	Philippe De Wilde
Date Deposited:	28 Jan 2026 14:37 UTC
Last Modified:	29 Jan 2026 14:22 UTC
Resource URI:	https://kar.kent.ac.uk/id/eprint/112900 (The current URI for this page, for reference purposes)

University of Kent Author Information

De Wilde, Philippe.

Creator's ORCID:	https://orcid.org/0000-0002-4332-1715
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