Towards Automating Fuzzy Rule Extraction for Fuzzy-BDI Agents in Cyber-Physical Systems


Guclu M., Karaduman B., TEZEL B. T., Challenger M.

7th International Conference on Intelligent and Fuzzy Systems, INFUS 2025, İstanbul, Turkey, 29 - 31 July 2025, vol.1528 LNNS, pp.698-706, (Full Text)

  • Publication Type: Conference Paper / Full Text
  • Volume: 1528 LNNS
  • Doi Number: 10.1007/978-3-031-97985-9_77
  • City: İstanbul
  • Country: Turkey
  • Page Numbers: pp.698-706
  • Keywords: Cyber-Physical System, Fuzzy Rule Extraction, Fuzzy-BDI Agents
  • Dokuz Eylül University Affiliated: Yes

Abstract

Cyber-Physical Systems (CPS) require intelligent agents capable of reasoning in uncertainty and adapting to dynamic environments. Fuzzy-BDI agents, which combine fuzzy logic with the Belief-Desire-Intention (BDI) paradigm, offer a robust solution but introduce additional complexity due to their hybrid nature. One of the most challenging aspects of their development is the manual creation of fuzzy rules from raw data collected by sensors, which is time-consuming and error-prone. This exploratory research proposes automating fuzzy rule extraction for fuzzy-BDI agents, streamlining the integration of fuzzy reasoning into BDI agents. The proposed approach involves extracting knowledge from the sampled data using machine learning algorithms to rigorously derive fuzzy rules, which are then embedded in the agent’s belief base. By automating this process, the framework reduces human effort, decreases time consumption, and improves the usability of fuzzy-BDI in CPS applications. The study is evaluated by comparing the manual definition of rules and the automated extraction of rules.