• Introduction and syllabus. Course website. Class policies and guidelines.
• Java AI program demos.
• Discussion on intelligence and artificial intelligence.
• AI categories/applications. AI programming.
• Turing test.
• Intelligent agents.
• Readings - Lucci & Kopec Chapter 1.

Monday, 8/28. Add/Drop and Late Registration via RAIL or at Ikenberry Hall.

Friday, 9/1. Last Day to Add/Drop or Late Register via RAIL or at Ikenberry Hall.

• "Classical AI" - top-down approaches.
• A problem solving framework - State. Operator. State space representation.
• State space search. Solution and solution path.
• Examples - 8-puzzle, knight's tour, and traveling-salesman problem.
• Exercise - 8-puzzle and water jug problems.
• Readings - Lucci & Kopec Chapter 2.

Monday, 9/4. Labor Day — Holiday.

Friday, 9/8. Last Day for Instructor-Approved Late Adds via RAIL.

• Examples and exercises cont. - Game of Nim and farmer/wolf/goat/cabbage puzzle. Optional - Syntax analysis and theorem proof.
• Search methods. Breadth-first, depth-first, and best-first searches.
• Heuristic search. Evaluation functions.
• Java implementation of the state space search framework.
• Structure, classes, and methods of the framework.
• Readings - Lucci & Kopec Chapters 2-4.

• Q/As on Java implementation of the state space search framework.

Exam 1 on Wednesday. Covers weeks #1-3.

• Java implementation of the state space search framework (cont.)
• Implementation of the water-jug problem.

• Dynamic programming search.
• 1D problem - Fibonacci numbers.
• 2D problem - coin change.
• Continuous knapsack problem. Procedure of greedy approaches.
• Exercises on dynamic programming search - Discrete knapsack problem.
• Readings - In-class examples.

• Discrete knapsack problem answer.

Mid-term Exam Week.

Friday, 10/13. Last Day to Apply for May 2018 Graduation (Registrar’s Office).

Exam 2 at 5pm on Wednesday. Covers weeks #4-6.

• Type and confidence of reasoning. Automated reasoning.
• Formal logics. Truth tables. Negation, conjunction, disjunction, and implication.
• Proofs of laws and formulas - de Morgan's, associative, and distributive laws.
• Predicate form. Conjunctive normal form (CNF). Clause form.
• Language representation of rules and facts. Examples and exercises - Happy student problem.
• Resolution refutation proofs. Inference methods - forward chaining and backward chaining. Exercises on CNFs and proofs.
• Fuzzy logic. Systems involving uncertainty/probability.
• Prisoner's dilemma problem. King's counterfeit coin problem.
• Readings - In-class examples. Lucci & Kopec Chapters 5 & 8.

Thursday & Friday, 10/19 & 10/20. Fall Break (or Make-up Days for Inclement Weather).

• Expert systems. Knowledge systems.
• Links to Prolog and Lisp interpreters.
• SWI Prolog reference manual.
• Introduction to Prolog. Recursion. Inference (is implied by).
• Conjunction and disjunction operators. Assignments/Statements.
• Examples/exercises - factorial, sum, exponential, and Fibonacci functions.
• Data structures in Prolog. List processing. Bar, head (car), and tail (cdr) operators.
• Examples/exercises - sum, length, append, reverse etc. list functions. Sample database.
• Case study - use Prolog to build a simple family tree (actually a graph). Starter database. Sample answers.
• Readings - In-class examples. Lucci & Kopec Chapter 9. Online resources for Prolog (see links).

Wednesday, 10/25. First Day of Academic Advisement for Continuing Students for Spring 2018.

Friday, 10/27. Last Day to Withdraw from a Full Semester Class — See Advisor by Noon.

• Introduction to machine learning. Supervised and unsupervised learning.
• Rote learning. Concept learning. Learning by observation, from advice, from analogy etc.
• Introduction to artificial neural networks (ANNs).
• Perceptron learning – one of the simplest neural networks. Delta learning rule.
• Single instance training example.
• Multiple-instance training example.
• Readings - In-class examples. Lucci & Kopec Chapter 11.

• Use matrixes to simplify the procedure for multiple-instance perceptrion training.
• Multiple-category classification method.
• Readings - In-class examples. Lucci & Kopec Chapter 11.

Monday, 11/6. First Day of Spring 2018 RAIL Registration for Continuing Students.

Wednesday, 11/8. Last Day of Academic Advisement for Continuing Students for Spring 2018.

Exam 3 on Wednesday. Covers weeks #7-10.

• Introduction to artificial memory.
• Hopfield network with one pattern.
• Hopfield network with multiple patterns.
• Implementation of Hopfield networks.
• Implementing a simple Hopfield network that memorizes two patterns.
• Example and exercise - 0 & 1 patterns. 2 simple patterns from exercise.
• Readings - In-class examples. Lucci & Kopec Chapter 11.

Thanksgiving Recess.

• Artificial intelligence inspired by natural behaviors and phenomena.
• Particle swarm optimization.
• Introduction to genetic algorithms.
• Concepts of gene, chromosome, individual, generation, crossover, and mutation. Selection based on fitness functions.
• Application of genetic algorithms to solve "hard" (e.g. NP-complete) problems.
• Example - CNF satisfiability problem. Traveling salesman problem (TSP).
• Readings - In-class examples. Lucci & Kopec Chapter 12.

• Implementation of genetic algorithms. Demos.
• Exercise - Implementation of the TSP problem.
• Summary of AI topics covered. Extensions.
• Final exam review.
• Readings - Lucci & Kopec Chapter 12.

Friday, 12/8. Last Day of Classes. Last Day for Complete Withdrawal from Semester.

Final Exam Week.

Final Exam -
9 – 11 am,
12/14, Thursday.