{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T15:44:45Z","timestamp":1781279085822,"version":"3.54.1"},"reference-count":18,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2022,9,20]],"date-time":"2022-09-20T00:00:00Z","timestamp":1663632000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Axioms"],"abstract":"<jats:p>An explainable artificial intelligence (XAI) agent is an autonomous agent that uses a fundamental XAI model at its core to perceive its environment and suggests actions to be performed. One of the significant challenges for these XAI agents is performing their operation efficiently, which is governed by the underlying inference and optimization system. Along similar lines, an Explainable Fuzzy AI Challenge (XFC 2022) competition was launched, whose principal objective was to develop a fully autonomous and optimized XAI algorithm that could play the Python arcade game \u201cAsteroid Smasher\u201d. This research first investigates inference models to implement an efficient (XAI) agent using rule-based fuzzy systems. We also discuss the proposed approach (which won the competition) to attain efficiency in the XAI algorithm. We have explored the potential of the widely used Mamdani- and TSK-based fuzzy inference systems and investigated which model might have a more optimized implementation. Even though the TSK-based model outperforms Mamdani in several applications, no empirical evidence suggests this will also be applicable in implementing an XAI agent. The experimentations are then performed to find a better-performing inference system in a fast-paced environment. The thorough analysis recommends more robust and efficient TSK-based XAI agents than Mamdani-based fuzzy inference systems.<\/jats:p>","DOI":"10.3390\/axioms11100489","type":"journal-article","created":{"date-parts":[[2022,9,20]],"date-time":"2022-09-20T21:12:53Z","timestamp":1663708373000},"page":"489","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Explainable Fuzzy AI Challenge 2022: Winner\u2019s Approach to a Computationally Efficient and Explainable Solution"],"prefix":"10.3390","volume":"11","author":[{"given":"Sunny","family":"Mishra","sequence":"first","affiliation":[{"name":"Department of Computer Science, South Asian University, New Delhi 110021, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Amit K.","family":"Shukla","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology, University of Jyvaskyla, P.O. Box 35 (Agora), 40014 Jyvaskyla, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7122-7622","authenticated-orcid":false,"given":"Pranab K.","family":"Muhuri","sequence":"additional","affiliation":[{"name":"Department of Computer Science, South Asian University, New Delhi 110021, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,9,20]]},"reference":[{"key":"ref_1","first-page":"44","article-title":"DARPA\u2019s explainable artificial intelligence (XAI) program","volume":"40","author":"Gunning","year":"2019","journal-title":"AI Mag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1109\/MC.2018.3620965","article-title":"Toward human-understandable, explainable AI","volume":"51","author":"Hagras","year":"2018","journal-title":"Computer"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3579","DOI":"10.1109\/TFUZZ.2021.3079503","article-title":"Critical thinking about explainable ai (XAI) for rule- based fuzzy systems","volume":"29","author":"Mendel","year":"2021","journal-title":"IEEE Trans. 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Available online: https:\/\/xfuzzycomp.pythonanywhere.com\/."}],"container-title":["Axioms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-1680\/11\/10\/489\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:34:49Z","timestamp":1760142889000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-1680\/11\/10\/489"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,20]]},"references-count":18,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["axioms11100489"],"URL":"https:\/\/doi.org\/10.3390\/axioms11100489","relation":{},"ISSN":["2075-1680"],"issn-type":[{"value":"2075-1680","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,20]]}}}