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    "Artificial Intelligence: Agent Behaviour I, Exercises II" by William John Teahan

    Posted By: exLib
    "Artificial Intelligence: Agent Behaviour I, Exercises II" by William John Teahan

    "Artificial Intelligence: Agent Behaviour Exercises II" by William John Teahan
    BoBoCoAe, WJT & Ventus Publishing ApS | 2010 | ISBN: 8776815927 9788776815929 | 202 pages | PDF | 6 MB

    The book is a series of exercises and NetLogo models (with source code and documentation)

    Contents
    Preface
    6. Behaviour
    6.1 What is behaviour?
    6.2 Reactive versus Cognitive Agents
    6.3 Emergence, Self-organisation, Adaptivity and Evolution
    6.4 The Frame of Reference Problem
    6.5 Stigmergy and Swarm Intelligence
    6.6 Implementing behaviour of Turtle Agents in NetLogo
    6.7 Boids
    7. Communication
    7.1 Communication, Information and Language
    7.2 The diversity of human language
    7.3 Communication via communities of agents
    7.4 Communicating Behaviour
    7.5 The Small World Phenomenon and Dijkstra’s algorithm
    7.6 Using communicating agents for searching networks
    7.7 Entropy and Information
    7.8 Calculating Entropy in NetLogo
    7.9 Language Modelling
    7.10 Entropy of a Language
    7.11 Communicating Meaning
    8. Search
    8.1 Search Behaviour
    8.2 Search Problems
    8.3 Uninformed (blind) search
    8.4 Implementing uninformed search in NetLogo
    8.5 Search as behaviour selection
    8.6 Informed search
    8.7 Local search and optimisation
    8.8 Comparing the search behaviours
    9. Knowledge
    9.1 Knowledge and Knowledge-based Systems
    9.2 Knowledge as justifi ed true belief
    9.3 Different types of knowledge
    9.4 Some approaches to Knowledge Representation and AI
    9.5 Knowledge engineering problems
    9.6 Knowledge without representation
    9.7 Representing knowledge using maps
    9.8 Representing knowledge using event maps
    9.9 Representing knowledge using rules and logic
    9.10 Reasoning using rules and logic
    9.11 Knowledge and reasoning using frames
    9.12 Knowledge and reasoning using decision trees
    9.13 Knowledge and reasoning using semantic networks
    10. Intelligence
    10.1 The nature of intelligence
    10.2 Intelligence without representation and reason
    10.3 What AI can and can’t do
    10.4 The Need for Design Objectives for Artifi cial Intelligence
    10.5 What are Good Objectives?
    10.6 Some Design Objectives for Artifi cial Intelligence
    10.7 Towards believable agents
    10.8 Towards computers with problem solving ability
    Solutions to Selected Exercises

    with TOC BookMarkLinks