Explainable Fuzzy AI Challenge 2022: Winner’s Approach to a Computationally Efficient and Explainable Solution

An explainable artificial intelligence (XAI) agent is an autonomous that uses a fundamental XAI model at its core to perceive environment and suggests actions be performed. One of the significant challenges for these agents performing their operation efficiently, which governed by underlying inference optimization system. Along similar lines, Explainable Fuzzy AI Challenge (XFC 2022) competition was launched, whose principal objective develop fully optimized algorithm could play Python arcade game “Asteroid Smasher”. This research first investigates models implement efficient using rule-based fuzzy systems. We also discuss proposed approach (which won competition) attain efficiency in algorithm. have explored potential widely used Mamdani- TSK-based systems investigated might more implementation. Even though outperforms Mamdani several applications, no empirical evidence this will applicable implementing agent. The experimentations are then performed find better-performing system fast-paced environment. thorough analysis recommends robust than Mamdani-based