{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T21:13:17Z","timestamp":1781125997277,"version":"3.54.1"},"reference-count":41,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T00:00:00Z","timestamp":1750377600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Artif. Intell."],"abstract":"<jats:p>This paper introduces a new approach to enhance the decision-making capabilities of the Tsetlin Machine (TM) through the Stochastic Point Location (SPL) algorithm and the Asymmetric Steps technique. We incorporate stochasticity and asymmetry into the TM's process, along with a decaying normal distribution function that improves adaptability as it converges toward zero over time. We present two methods: the Asymmetric Probabilistic Tsetlin (APT) Machine, influenced by random events, and the Asymmetric Tsetlin (AT) Machine, which transitions from probabilistic to deterministic states. We evaluate these methods against traditional machine learning algorithms and classical Tsetlin (CT) machines across various benchmark datasets. Both AT and APT demonstrate competitive performance, with the AT model notably excelling, especially in complex datasets.<\/jats:p>","DOI":"10.3389\/frai.2025.1377944","type":"journal-article","created":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T14:26:33Z","timestamp":1750429593000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Stochastic and deterministic processes in Asymmetric Tsetlin Machine"],"prefix":"10.3389","volume":"8","author":[{"given":"Negar","family":"Elmisadr","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamed-Bachir","family":"Belaid","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anis","family":"Yazidi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2025,6,20]]},"reference":[{"key":"B1","first-page":"268","article-title":"\u201cThe regression tsetlin machine: a tsetlin machine for continuous output problems,\u201d","volume-title":"Proceedings of the Progress in Artificial Intelligence","author":"Abeyrathna","year":"2019"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1111\/exsy.12836","article-title":"A multi-step finite-state automaton for arbitrarily deterministic Tsetlin machine learning","author":"Abeyrathna","year":"2021","journal-title":"arXiv"},{"key":"B3","article-title":"The regression tsetlin machine: a novel interpretable approach to regression","author":"Abeyrathna","year":"2022","journal-title":"Front. Artif. Intell."},{"key":"B4","doi-asserted-by":"publisher","first-page":"2699","DOI":"10.1007\/s10489-018-01399-9","article-title":"On solving the SPL problem using the concept of probability flux","volume":"49","author":"Abolpour Mofrad","year":"2019","journal-title":"Appl. Intellig"},{"key":"B5","first-page":"236","article-title":"\u201cAdaptive intelligence for batteryless sensors using software-accelerated Tsetlin machines,\u201d","volume-title":"Proceedings of the Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems","author":"Bakar","year":"2022"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1985.6313371","article-title":"Pattern-recognizing stochastic learning automata","author":"Barto","year":"1985","journal-title":"IEEE Trans. Syst. Man Cybern"},{"key":"B7","first-page":"3761","article-title":"\u201cConvTextTM: an explainable convolutional Tsetlin machine framework for text classification,\u201d","volume-title":"13th Language Resources and Evaluation Conference (LREC 2022)","author":"Bhattarai","year":"2022"},{"key":"B8","doi-asserted-by":"publisher","DOI":"10.1111\/j.1539-6924.2012.01792.x","article-title":"Confronting deep uncertainties in risk analysis","author":"Cox Jr","year":"2012","journal-title":"Risk Analy. Int. J"},{"key":"B9","doi-asserted-by":"publisher","first-page":"1687814018755519","DOI":"10.1177\/1687814018755519","article-title":"Machine learning techniques for quality control in high conformance manufacturing environment","volume":"10","author":"Escobar","year":"2018","journal-title":"Adv. Mecha. Eng"},{"key":"B10","doi-asserted-by":"publisher","first-page":"1768","DOI":"10.1109\/TPAMI.2006.233","article-title":"Random walks for image segmentation","volume":"28","author":"Grady","year":"2006","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell"},{"key":"B11","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1804.01508","article-title":"The tsetlin machine-a game theoretic bandit driven approach to optimal pattern recognition with propositional logic","author":"Granmo","year":"2018","journal-title":"arXiv"},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1905.09688","article-title":"The convolutional Tsetlin machine","author":"Granmo","year":"2019","journal-title":"arXiv"},{"key":"B13","doi-asserted-by":"publisher","first-page":"545","DOI":"10.1109\/TC.2009.189","article-title":"Solving stochastic nonlinear resource allocation problems using a hierarchy of twofold resource allocation automata","volume":"59","author":"Granmo","year":"2010","journal-title":"IEEE Trans. Comp"},{"key":"B14","doi-asserted-by":"publisher","first-page":"671","DOI":"10.1016\/0893-6080(90)90056-Q","article-title":"A stochastic reinforcement learning algorithm for learning real-valued functions","volume":"3","author":"Gullapalli","year":"1990","journal-title":"Neural Netw"},{"key":"B15","doi-asserted-by":"publisher","first-page":"3263","DOI":"10.1109\/JIOT.2017.2711426","article-title":"A new learning automata-based pruning method to train deep neural networks","volume":"5","author":"Guo","year":"2017","journal-title":"IEEE Intern. Things J"},{"key":"B16","doi-asserted-by":"crossref","first-page":"215","DOI":"10.1109\/DSC.2016.41","article-title":"\u201cA general strategy for solving the stochastic point location problem by utilizing the correlation of three adjacent nodes,\u201d","volume-title":"Proceedings of the 2016 IEEE First International Conference on Data Science in Cyberspace (DSC)","author":"Guo","year":"2016"},{"key":"B17","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1145\/1412228.1412237","article-title":"An experimental study of point location in planar arrangements in CGAL","volume":"13","author":"Haran","year":"2009","journal-title":"J. Exp. Algorithm"},{"key":"B18","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s00170-011-3360-0","article-title":"Stochastic models for transfer point location problem","volume":"58","author":"Hosseinijou","year":"2012","journal-title":"Int. J. Adv. Manuf. Technol"},{"key":"B19","first-page":"61","article-title":"A novel survey on location based node detection and identifying the malicious activity of nodes in sensor networks","volume":"8","author":"Karthik","year":"2017","journal-title":"Int. J. Comp. Eng. Technol"},{"key":"B20","doi-asserted-by":"publisher","first-page":"103168","DOI":"10.1016\/j.cose.2023.103168","article-title":"Multi-targeted audio adversarial example for use against speech recognition systems","volume":"128","author":"Ko","year":"2023","journal-title":"Comput. Secur."},{"key":"B21","doi-asserted-by":"publisher","first-page":"1377913795","DOI":"10.1007\/s11042-022-12941-w","article-title":"Adversarial image perturbations with distortions weighted by color on deep neural networks","volume":"82","author":"Kwon","year":"2023","journal-title":"Multimed. Tools Appl."},{"key":"B22","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3245632","article-title":"Dual-mode method for generating adversarial examples to attack deep neural networks","author":"Kwon","year":"2023","journal-title":"IEEE Access"},{"key":"B23","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3216075","article-title":"Audio adversarial example detection using the audio style transfer learning method","author":"Kwon","year":"2023","journal-title":"IEEE Access."},{"key":"B24","doi-asserted-by":"publisher","first-page":"1916119185","DOI":"10.1007\/s10489-022-03313-w","article-title":"Detecting textual adversarial examples through text modification on text classification systems","volume":"53","author":"Kwon","year":"2023","journal-title":"Appl. Intell."},{"key":"B25","doi-asserted-by":"publisher","first-page":"103061","DOI":"10.1016\/j.cose.2022.103061","article-title":"Audio adversarial detection through classification score on speech recognition systems","volume":"126","author":"Kwon","year":"2023","journal-title":"Comput. Secur."},{"key":"B26","volume-title":"Robust Learning for Autonomous Agents in Stochastic Environments","author":"Lecerf","year":"2022"},{"key":"B27","doi-asserted-by":"publisher","first-page":"1124598","DOI":"10.1155\/2024\/1124598","article-title":"Evasion attacks on deep learning? Based helicopter recognition systems","volume":"1","author":"Lee","year":"2024","journal-title":"J. Sens."},{"key":"B28","first-page":"71","article-title":"\u201cLearning automata as a basis for multi-agent reinforcement learning,\u201d","author":"Now\u00e9","year":"2005","journal-title":"Proceedings of the International Workshop on Learning and Adaption in Multi-Agent Systems"},{"key":"B29","first-page":"775","article-title":"\u201cEnhancing the speed of hierarchical learning automata by ordering the actions-a pioneering approach,\u201d","volume-title":"35th Australasian Joint Conference on Artificial Intelligence (AI 2022)","author":"Omslandseter","year":"2022"},{"key":"B30","doi-asserted-by":"publisher","first-page":"733","DOI":"10.1109\/3477.604122","article-title":"Stochastic searching on the line and its applications to parameter learning in nonlinear optimization","volume":"27","author":"Oommen","year":"1997","journal-title":"IEEE Trans. Syst. Man, Cybernet. Part B (Cybernetics)"},{"key":"B31","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1911.12607","article-title":"The weighted tsetlin machine: compressed representations with weighted clauses","author":"Phoulady","year":"2019","journal-title":"arXiv"},{"key":"B32","doi-asserted-by":"publisher","DOI":"10.1109\/ISTM58889.2023.10454997","article-title":"Verifying properties of Tsetlin machines","author":"Przybysz","year":"2023","journal-title":"arXiv"},{"key":"B33","first-page":"173","article-title":"\u201cExplainable reinforcement learning with the Tsetlin machine,\u201d","volume-title":"34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA\/AIE 2021)","author":"Rahimi Gorji","year":"2021"},{"key":"B34","doi-asserted-by":"publisher","first-page":"e12873","DOI":"10.1111\/exsy.12873","article-title":"Using Tsetlin machine to discover interpretable rules in natural language processing applications","volume":"40","author":"Saha","year":"2023","journal-title":"Expert Syst"},{"key":"B35","doi-asserted-by":"publisher","first-page":"160","DOI":"10.1007\/s42979-021-00592-x","article-title":"Machine learning: Algorithms, real-world applications and research directions","volume":"2","author":"Sarker","year":"2021","journal-title":"SN comp. Sci"},{"key":"B36","first-page":"404","article-title":"\u201cCenter-piece subgraphs: problem definition and fast solutions,\u201d","volume-title":"Proceedings of the Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","author":"Tong","year":"2006"},{"key":"B37","first-page":"774","article-title":"\u201cA hierarchical learning scheme for solving the stochastic point location problem,\u201d","volume-title":"Proceedings of the Advanced Research in Applied Artificial Intelligence: 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA\/AIE 2012","author":"Yazidi","year":"2012"},{"key":"B38","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1109\/ICTCS.2017.70","article-title":"\u201cThe theory and applications of the Stochastic point location problem,\u201d","volume-title":"2017 International Conference on New Trends in Computing Sciences (ICTCS)","author":"Yazidi","year":"2017"},{"key":"B39","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1016\/j.ins.2017.02.014","article-title":"A novel technique for stochastic root-finding: enhancing the search with adaptive d-ary search","volume":"393","author":"Yazidi","year":"2017","journal-title":"Inf. Sci"},{"key":"B40","doi-asserted-by":"publisher","first-page":"5403","DOI":"10.1109\/TCYB.2021.3119591","article-title":"Extension of Stochastic point location for multimodal problems","volume":"53","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Cybernet"},{"key":"B41","doi-asserted-by":"publisher","first-page":"626","DOI":"10.1109\/TCYB.2016.2521859","article-title":"Symmetrical hierarchical stochastic searching on the line in informative and deceptive environments","volume":"47","author":"Zhang","year":"2016","journal-title":"IEEE Trans. Cybern"}],"container-title":["Frontiers in Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/frai.2025.1377944\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,20]],"date-time":"2025-06-20T14:26:39Z","timestamp":1750429599000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/frai.2025.1377944\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,20]]},"references-count":41,"alternative-id":["10.3389\/frai.2025.1377944"],"URL":"https:\/\/doi.org\/10.3389\/frai.2025.1377944","relation":{},"ISSN":["2624-8212"],"issn-type":[{"value":"2624-8212","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,20]]},"article-number":"1377944"}}