--------------------------------------------------------------------- R&N R&N Second edition First edition Part I Artificial Intelligence Part I Artificial Intelligence 1 Introduction 1 Introduction 2 Intelligent Agents 2 Intelligent Agents Part II Problem Solving Part II Problem Solving 3 Solving Problems by Searching 3 Solving Problems by Searching 4 Informed Search and Exploration 4 Informed Search Methods 5 Constraint Satisfaction Problems (waaronder CS) 6 Adversarial Search 5 Game Playing 7. Logical Agents 6 Agents that reason logically 8. First-order logic 7 First-order logic 9. Inference in First-Order Logic 9 Inference in First-Order Logic 10. Knowledge Representation 8 Building a knowledge base (logical reasoning zit in hfdst 7) 10 Logical reasoning 11. + 12. PLANNING: NIET 11 + 12 + 13. PLANNING: NIET 13. Uncertainty 14 Uncertainty 14 Probabilistic Reasoning 15 Probabilistic Reasoning 15 (spraak e.d.) NIET - 16 Making Simple Decisions 16 Making Simple Decisions 17 Making Complex Decisions 17 Making Complex Decision 18 Learning from Observations 18 Learning from Observations ---------------------------------------------------------------------
Van belang is een goed begrip in het waarom van de 'agent architecture'. Je moet onderscheid kunnen maken tussen de verschillende zoekalgoritmes en hun kenmerkend gebruik van rekenkracht en geheugen. Wanneer pas je elke variant van de zoekalgoritmen toe? Hoe komen zoekruimtes tot stand (handmatig ontwikkelde kennisbestanden vs machine learning). Constraint satisfaction (deterministisch vs simulated annealing). Gebruik van predikatenlogica in de AI: wat kun je ermee, waarom is het van belang? Modellen van de wereld. Forward- en Backward chaining. Bayes en Belief Networks. Decision tree learning. |