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Lecture Multiagent systems - Chapter 2: Intelligent agents

The aim of this chapter is to give you an understanding of what agents are, and some of the issues associated with building them. In later chapters, we will see specific approaches to building agents. | LECTURE 2: INTELLIGENT AGENTS An Introduction to MultiAgent Systems http://www.csc.liv.ac.uk/~mjw/pubs/imas What is an Agent? The main point about agents is they are autonomous: capable of acting independently, exhibiting control over their internal state Thus: an agent is a computer system capable of autonomous action in some environment in order to meet its design objectives SYSTEM ENVIRONMENT input output What is an Agent? Trivial (non-interesting) agents: thermostat UNIX daemon (e.g., biff) An intelligent agent is a computer system capable of flexible autonomous action in some environment By flexible, we mean: reactive pro-active social Reactivity If a program’s environment is guaranteed to be fixed, the program need never worry about its own success or failure – program just executes blindly Example of fixed environment: compiler The real world is not like that: things change, information is incomplete. Many (most?) interesting environments are dynamic Software is hard to | LECTURE 2: INTELLIGENT AGENTS An Introduction to MultiAgent Systems http://www.csc.liv.ac.uk/~mjw/pubs/imas What is an Agent? The main point about agents is they are autonomous: capable of acting independently, exhibiting control over their internal state Thus: an agent is a computer system capable of autonomous action in some environment in order to meet its design objectives SYSTEM ENVIRONMENT input output What is an Agent? Trivial (non-interesting) agents: thermostat UNIX daemon (e.g., biff) An intelligent agent is a computer system capable of flexible autonomous action in some environment By flexible, we mean: reactive pro-active social Reactivity If a program’s environment is guaranteed to be fixed, the program need never worry about its own success or failure – program just executes blindly Example of fixed environment: compiler The real world is not like that: things change, information is incomplete. Many (most?) interesting environments are dynamic Software is hard to build for dynamic domains: program must take into account possibility of failure – ask itself whether it is worth executing! A reactive system is one that maintains an ongoing interaction with its environment, and responds to changes that occur in it (in time for the response to be useful) Proactiveness Reacting to an environment is easy (e.g., stimulus response rules) But we generally want agents to do things for us Hence goal directed behavior Pro-activeness = generating and attempting to achieve goals; not driven solely by events; taking the initiative Recognizing opportunities Balancing Reactive and Goal-Oriented Behavior We want our agents to be reactive, responding to changing conditions in an appropriate (timely) fashion We want our agents to systematically work towards long-term goals These two considerations can be at odds with one another Designing an agent that can balance the two remains an open research problem Social Ability The real world is a multi-agent