Abstract
Using the Jason framework and the CArtAgO platform, this study introduces a fresh paradigm for upgrading software agents in Cyber-Physical Systems (CPS) and the Internet of Things (IoT). We integrate Fuzzy Inference Systems (FIS) into the agents’ decision-making processes using Fuzzy Logic Controllers (FLCs) within the JaCa environment. This collaboration seeks to resolve uncertainty in real-world CPS and IoT contexts, allowing agents to make context-aware and adaptable judgements. Our method improves agent adaptation by allowing for more nuanced responses to changing situations. The efficacy of this integration is demonstrated experimentally, with enhanced interoperability and responsiveness. This study advances intelligent agent systems by presenting a possible path for generating more context-aware agents in the dynamic landscape of CPS and IoT, encouraging efficient and adaptive autonomous systems.
Keywords: CPS, FLC, Intelligent Agent, IoT, JaCa.