多智能体系统

The course aims to provide a comprehensive and integrativeperspective on Multi-Agent Systems (MAS) and Artificial Intelligence (AI),bridging the gap between foundational theories and advanced methodologies inthese fields. It is meticulously designed to cultivate a deep understanding ofMAS, encompassing both traditional elements and innovative practices influencedby the latest advancements in AI. Students will explore the core principles ofMAS, including agent communication, coordination, and cooperation, alongsideadvanced topics such as intelligent optimization and decision-making. Through acombination of lectures and hands-on lab sessions, the course will delve intothe application of algorithms like Particle Swarm Optimization (PSO) and AntColony Optimization (ACO) within MAS, as well as advanced AI strategies likeNeuroEvolution of Augmenting Topologies (NEAT) and Genetic Programming (GP). Byintegrating theoretical knowledge with practical application, the courseprepares students to tackle complex, real-world problems using MAS and AI. Itaims to equip students with the skills necessary to design, implement, andevaluate intelligent systems, fostering a blend of analytical thinking andinnovative problem-solving.