This book is the second in a series on Artificial Intelligence. It adopts a behaviour-based approach to the design of agent-oriented systems. Topics covered from a behaviour-based perspective include agent communication, searching, knowledge and reasoning, and intelligence. Accompanying the book is a series of exercises and NetLogo models (with source code and documentation) which can be run directly from an applet or downloaded.

1. Behaviour
   1. What is behaviour?
   2. Reactive versus Cognitive Agents
   3. Emergence, Self-organisation, Adaptivity and Evolution
   4. The Frame of Reference Problem
   5. Stigmergy and Swarm Intelligence
   6. Implementing behaviour of Turtle Agents in NetLogo
   7. Boids
   8. Summary
2. Communication
   1. Communication, Information and Language
   2. The diversity of human language
   3. Communication via communities of agents
   4. Communicating Behaviour
   5. The Small World Phenomenon and Dijkstra’s algorithm
   6. Using communicating agents for searching networks
   7. Entropy and Information
   8. Calculating Entropy in NetLogo
   9. Language Modelling
   10. Entropy of a Language
   11. Communicating Meaning
   12. Summary
3. Search
   1. Search Behaviour
   2. Search Problems
   3. Uninformed (blind) search
   4. Implementing uninformed search in NetLogo
   5. Search as behaviour selection
   6. Informed search
   7. Local search and optimisation
   8. Comparing the search behaviours
   9. Summary and Discussion
4. Knowledge
   1. Knowledge and Knowledge-based Systems
   2. Knowledge as justified true belief
   3. Different types of knowledge
   4. Some approaches to Knowledge Representation and AI
   5. Knowledge engineering problems
   6. Knowledge without representation
   7. Representing knowledge using maps
   8. Representing knowledge using event maps
   9. Representing knowledge using rules and logic
   10. Reasoning using rules and logic
   11. Knowledge and reasoning using frames
   12. Knowledge and reasoning using decision trees
   13. Knowledge and reasoning using semantic networks
   14. Summary and Discussion
5. Intelligence
   1. The nature of intelligence
   2. Intelligence without representation and reason
   3. What AI can and can’t do
   4. The Need for Design Objectives for Artificial Intelligence
   5. What are Good Objectives?
   6. Some Design Objectives for Artificial Intelligence
   7. Towards believable agents
   8. Towards computers with problem solving ability
   9. Summary and Discussion
6. References