Section 1: Intelligent Agents

Key Learning Points

• Describe what is meant by the term agent.
• Discuss the architecture for agents.
• Describe the various major design approaches that one can follow in implementing an agent system.

Activities

1. Read Wooldridge, M. (1999). Intelligent agents. In G. Weiss (Ed.), Multiagent systems: A modern approach to distributed artificial intelligence (pp. 27–79). Cambridge, MA: The MIT Press.
2. Watch the following videos by M. Wooldridge on Multiagent Systems:
   1. Introducing Multiagent Systems
   2. Objections to Multiagent Systems
   3. Agent and Environment: The Sense-Decide-Act Loop
   4. Properties of Intelligent Agents
   5. Objects and Agents
   6. All About an Agent’s Environment
   7. Agents as Intentional Systems
   8. A Formal Model of Agents and Environments
   9. Perception, Action, and State
   10. How to tell an agent what to do (without telling it how to do it)
   11. Agent Architectures
   12. Deductive Reasoning Agents
   13. Agent-Oriented Programming and Agent0
   14. Concurrent Metatem—A Logic-based Multiagent Programming Language
   15. Practical Reasoning Agents

3. Complete the exercises.

   Give two examples of agents (not necessarily intelligent) that you know of. For each, define as precisely as possible: (a) the environment that agent occupies (physical, software, etc.); the states that this environment can be in; and whether the environment is accessible or inaccessible, deterministic or non-deterministic, episodic or non-episodic, static or dynamic, and discrete or continuous. (b) the action repertoire available to the agent and any preconditions associated with these actions. (c) the goal or design objectives of the agent: what does it intend to achieve?

4. Discuss the following questions in the discussion forum: What are the similarities and differences between an agent and an object? What are the similarities and differences between an agent and an expert system?