Artificial Intelligence - Agent Behaviour I [math]

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. You can download the book for free via the link below. Content 1. Behaviour 1.1. What is behaviour? 1.2. Reactive versus Cognitive Agents 1.3. Emergence, Self-organisation, Adaptivity and Evolution 1.4. The Frame of Reference Problem 1.5. Stigmergy and Swarm Intelligence 1.6. Implementing behaviour of Turtle Agents in NetLogo 1.7. Boids 1.8. Summary 2. Communication 2.1. Communication, Information and Language 2.2. The diversity of human language 2.3. Communication via communities of agents 2.4. Communicating Behaviour 2.5. The Small World Phenomenon and Dijkstra’s algorithm 2.6. Using communicating agents for searching networks 2.7. Entropy and Information 2.8. Calculating Entropy in NetLogo 2.9. Language Modelling 2.10. Entropy of a Language 2.11. Communicating Meaning 2.12. Summary 3. Search 3.1. Search Behaviour 3.2. Search Problems 3.3. Uninformed (blind) search 3.4. Implementing uninformed search in NetLogo 3.5. Search as behaviour selection 3.6. Informed search 3.7. Local search and optimisation 3.8. Comparing the search behaviours 3.9. Summary and Discussion 4. Knowledge 4.1. Knowledge and Knowledge-based Systems 4.2. Knowledge as justified true belief 4.3. Different types of knowledge 4.4. Some approaches to Knowledge Representation and AI 4.5. Knowledge engineering problems 4.6. Knowledge without representation 4.7. Representing knowledge using maps 4.8. Representing knowledge using event maps 4.9. Representing knowledge using rules and logic 4.10. Reasoning using rules and logic 4.11. Knowledge and reasoning using frames 4.12. Knowledge and reasoning using decision trees 4.13. Knowledge and reasoning using semantic networks 4.14. Summary and Discussion 5. Intelligence 5.1. The nature of intelligence 5.2. Intelligence without representation and reason 5.3. What AI can and can’t do 5.4. The Need for Design Objectives for Artificial Intelligence 5.5. What are Good Objectives? 5.6. Some Design Objectives for Artificial Intelligence 5.7. Towards believable agents 5.8. Towards computers with problem solving ability 5.9. Summary and Discussion 6. References Sisältö Behaviour What is behaviour? Reactive versus Cognitive Agents Emergence, Self-organisation, Adaptivity and Evolution The Frame of Reference Problem Stigmergy and Swarm Intelligence Implementing behaviour of Turtle Agents in NetLogo Boids Summary Communication Communication, Information and Language The diversity of human language Communication via communities of agents Communicating Behaviour The Small World Phenomenon and Dijkstra’s algorithm Using communicating agents for searching networks Entropy and Information Calculating Entropy in NetLogo Language Modelling Entropy of a Language Communicating Meaning Summary Search Search Behaviour Search Problems Uninformed (blind) search Implementing uninformed search in NetLogo Search as behaviour selection Informed search Local search and optimisation Comparing the search behaviours Summary and Discussion Knowledge Knowledge and Knowledge-based Systems Knowledge as justified true belief Different types of knowledge Some approaches to Knowledge Representation and AI Knowledge engineering problems Knowledge without representation Representing knowledge using maps Representing knowledge using event maps Representing knowledge using rules and logic Reasoning using rules and logic Knowledge and reasoning using frames Knowledge and reasoning using decision trees Knowledge and reasoning using semantic networks Summary and Discussion Intelligence The nature of intelligence Intelligence without representation and reason What AI can and can’t do The Need for Design Objectives for Artificial Intelligence What are Good Objectives? Some Design Objectives for Artificial Intelligence Towards believable agents Towards computers with problem solving ability Summary and Discussion References Obsah Behaviour What is behaviour? Reactive versus Cognitive Agents Emergence, Self-organisation, Adaptivity and Evolution The Frame of Reference Problem Stigmergy and Swarm Intelligence Implementing behaviour of Turtle Agents in NetLogo Boids Summary Communication Communication, Information and Language The diversity of human language Communication via communities of agents Communicating Behaviour The Small World Phenomenon and Dijkstra’s algorithm Using communicating agents for searching networks Entropy and Information Calculating Entropy in NetLogo Language Modelling Entropy of a Language Communicating Meaning Summary Search Search Behaviour Search Problems Uninformed (blind) search Implementing uninformed search in NetLogo Search as behaviour selection Informed search Local search and optimisation Comparing the search behaviours Summary and Discussion Knowledge Knowledge and Knowledge-based Systems Knowledge as justified true belief Different types of knowledge Some approaches to Knowledge Representation and AI Knowledge engineering problems Knowledge without representation Representing knowledge using maps Representing knowledge using event maps Representing knowledge using rules and logic Reasoning using rules and logic Knowledge and reasoning using frames Knowledge and reasoning using decision trees Knowledge and reasoning using semantic networks Summary and Discussion Intelligence The nature of intelligence Intelligence without representation and reason What AI can and can’t do The Need for Design Objectives for Artificial Intelligence What are Good Objectives? Some Design Objectives for Artificial Intelligence Towards believable agents Towards computers with problem solving ability Summary and Discussion References Cover......Page 1 Artificial Intelligence – Agent Behaviour I......Page 2 ©......Page 3 Contents......Page 4 6. Behaviour......Page 7 7. Communication......Page 49 8. Search......Page 96 9. Knowledge......Page 138 10. Intelligence......Page 199 References......Page 233