Artificial Intelligence - Exercises - Agent Behaviour I [math]

Artificial Intelligence, or AI, is the study and development of computer systems which can perform tasks which normally require human intelligence. Agent Behaviour is a complex aspect of AI, but integral to one’s understanding of the subject. You can download the book for free via the link below. 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 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 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 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 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 Solutions to Selected Exercises 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 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 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 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 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 Solutions to Selected Exercises Cover......Page 1 Artificial Intelligence: Agent Behaviour I, Exercises II......Page 2 ©......Page 3 Contents......Page 4 Exercises for Artificial Intelligence – Agent Behaviour I......Page 7 Preface......Page 8 6. Behaviour......Page 13 7. Communication......Page 47 8. Search......Page 84 9. Knowledge......Page 117 10. Intelligence......Page 147