Profile
This course covers an introduction to intelligent agents and multi-agent systems. Students will learned the fundamental understanding of key concepts for agent-based systems, such as reasoning and architectures, cooperative distributed problem solving, and the important concepts in game theory for benevolent and self-interested agents to work together.
What You'll Learn
Upon completion of the course, students should be able to:a) Understand the variety of connotations that agent-based computation implies and appreciate how the field fits into Artificial Intelligence and more broadly, Computer Science.b) Understand how the importance of reasoning and how this can be incorporated into an embodied agent. Differentiate and motivate various agent architectures. Understand the historical development of the agent architecture field.c) Comprehend the complexity that a multi-agent system entails and the difference between benevolent and self-interested agents, and understand how benevolent agents work together to perform distributed problem solving.d) Appreciate the value of game theory when applied to multi-agent systems populated by self-interested agents, and understand how these agents interact with each other and make decisions.e) Gain awareness of several advanced applications of intelligent agents and multi-agent systems such as interface agents, e-commerce agents, workflow and business process management, distributed sensing, multi-agent based electronic marketplaces, multi-agent based vehicular ad hoc networks etc.