Intelligent Agents and Neural Fuzzy Logic: Enhancing Agent Intelligence in Complex Environments
Shorouq Elmanaseer, Wael Alzyadat · 2023
Intelligent agents have become increasingly significant in numerous fields including autonomous systems, robotics, and smart environments. Neural fuzzy logic, an amalgamation of fuzzy logic and neural networks, offers a propitious solution to incumbent-addressed roadblocks to sub-optimal decision-making and limited adaptability. This paper presents a methodology for integrating neural fuzzy logic into intelligent agent systems, with a focus on a case study involving a robotic vacuum cleaner, constructing a smart cleaning device that continues to learn and optimize its cleaning performance based on experiences. The proposed approach leverages the power of neural fuzzy logic and robotics to create an intelligent and adaptive cleaning device. The iterative nature of the proposed approach allows the robot vacuum cleaner to continuously adapt its behavior based on real-time feedback and learning capabilities, enhancing the intelligence and autonomy of the agent.