Root View:Course ComponentsSyllabus

jumpThe course syllabus establishes course policies on grading, attendance, and exams. The syllabus should be read in detail at beginning semester. Calendar

jumpThe course calendar provides a summary temporal view of the course, including textbook coverage, assignments, and due dates. Note that each week in the calendar has a Detailslink where the assignment is released and any supplemental links are published.My FSU

new windowThe FSU/Blackboard Portal, where you will find this course. The course site is the main communication resource for the class. Here you can get help, talk to other students, retrieve your grades, and generally keep up with course news and announcements. Textbook

new windowThe textbook for the course is Artificial Intelligence, A Modern Approach, Second Edition, by Stuart Russell and Peter Norvig, Prentice Hall, 2003 (ISBN 0-13-790395-2). Cited as [AIMA].Assignments

see weekly detailsAssignments will be released through the weekly Details expansion linked from the Calendar. Assignment submission instructions are below. Lectures

see weekly detailsSome lecture slides have been prepared for this course by the original creator, Dr. Ernest McDuffie. These will be updated and published when appropriate. Acknowledgments This course was designed, created, and originally taught by Dr. Ernest McDuffie, who is currently with the US Office of Naval Research. Dr. McDuffie is fondly remembered and severely missed by the CS faculty, staff, and students. We are honored to continue to enjoy his collegiality and friendship. Most of the lecture slides (with only slight modification) are from Dr. McDuffie's originals, as are all of the weekly course objectives. The format of the calendar and "weekly details" elaborations are also based on Dr. McDuffie's design (where it was a paper document).

Temporal View:Course CalendarWeekDatesCoverageAssignmentDue Date1 Details 8/23 - 8/29 Ch 1 Hw 1 9/5 2 Details 8/30 - 9/5 Ch 2 Hw 1 9/5 3 Details 9/6 - 9/12 Ch 3 Hw 2 9/19 4 Details 9/13 - 9/19 Ch 4 Hw 2 9/19 5 Details 9/20 - 9/26 Ch 7 Hw 3 10/10 6 Details 9/27 - 10/3 Ch 8 Hw 3 10/10 7 Details 10/4 - 10/10 Ch 9 Hw 3 10/10 8 10/11 - 10/17 Midterm Exam: See Syllabus for policy and schedule 9 Details 10/18 - 10/24 Ch 10 Hw 4 11/7 10 Details 10/25 - 10/31 Ch 11, 12 Hw 4 11/7 11 Details 11/1 - 11/7 Ch 13, 14 Hw 4 11/7 12 Details 11/8 - 11/14 Ch 16 Hw 5 11/28 13 Details 11/15 - 11/21 Ch 18 Hw 5 11/28 14 Details 11/22 - 11/28 Ch 20 Hw 5 11/28 15 Details 11/29 - 12/5 Ch 26, 27 NA NA 16 12/6 - 12/12 Final Exam: See Syllabus for policy and schedule 17 12/13 - 1/2 Semester Break: Have a wonderful holiday.

Details:Week 1Topic:Artificial Intelligence: Introduction Objectives:

- Characterize AI definitions according to specified dimensions.
- Decide whether computers can accomplish specified tasks according to the current literature.
- Discuss the concept of intelligence as it relates to computers.
- Discuss the concept of intelligence as it relates to animals.
- Discuss the difference between a performance measure and a utility function.
Reading:Chapter 1 of [AIMA] Supplemental:McDuffie Lecture Slides Assignment:Homework 1 (partial): Exercises 1.1, 1.3, 1.7, 1.10, 1.11 Items Due:No deliverables this week, but you should complete the portion of the assignment from Chapter 1.

Details:Week 2Topic:Artificial Intelligence: Intelligent Agents Objectives:

- Given an environment, decide which agent is most appropriate.
- Describe an agent that is appropriate for a familiar domain.
- Given a list of policies, decide which is best. Discuss how you reached the decision.
- Given a domain, calculate the size of the table for a look-up agent.
- Discuss the sequential relationship between goal formulation and problem formulation.
Reading:Chapter 2 of [AIMA] Supplemental:McDuffie Lecture Slides Assignment:Homework 1 (continued): Exercises 2.1, 2.2, 2.3, 2.4, 2.5 Items Due:Homework 1

Details:Week 3Topic:Problem Solving: Solving Problems by Searching Objectives:

- Given a problem set, determine the following: initial state, goal test, operators, and path cost function for each problem.
- Write and apply a version of the General-Search algorithm.
- Describe a search space in which iterative deepening search performs much worse than depth-first search.
- Given a bidirectional search, describe an alternative direction to the breadth-first search.
- Given a greedy search algorithm with h(n)= -g(n), describe the search that the greedy search will emulate.
Reading:Chapter 3 of AIMA Supplemental:McDuffie Lecture Slides

candyAssignment:Homework 2 (partial): Exercises 3.1, 3.2, 3.5, 3.8, 3.9 Items Due:No items due, but the first half of Homework 2 has been assigned.

Details:Week 4Topic:Problem Solving: Informed Search and Exploration Objectives:

- Given a situation in which no good evaluation function for a problem exists, show that a comparison method is appropriate for a best-first search.
- Given that an admissible heuristic leads to monotonically nondecreasing f values along any path, discuss whether the implication goes the other way.
- Discuss features of a bidirectional A* search.
Reading:Chapters 4 of AIMA Supplemental:McDuffie Lecture Slides, Part a Slides only available in pdf format, the PP source has been lost

McDuffie Lecture Slides, Part b Slides only available in pdf format, the PP source has been lostAssignment:Homework 2 (continued): Exercises 4.1, 4.2, 4.3, 4.12 Items Due:Homework 2

Details:Week 5Topic:Knowledge and Reasoning: Logical Agents, Propositional Logic Objectives:

- Describe how to use a truth table to decide whether a given sentence is valid, satisfiable, or unsatisfiable.
- Given a set of sentences, use truth tables to show that each sentence is valid and that the equivalences hold.
- Given a set of sentences, decide whether each is valid, unsatisifiable, or neither using truth tables or equivalence rules.
- Given a series of if-then statements about a unicorn, discuss whether the following qualities of the unicorn are provable: mythical, magical, horned.
Reading:Chapter 7 of AIMA Supplemental:Assignment:Homework 3 (first third): Exercises 7.1, 7.4, 7.8, 7.9 Items Due:No items due, but the first part of Homework 3 has been assigned.

Details:Week 6Topic:Knowledge and Reasoning: First-Order Logic Objectives:

- Given a set of sentences, represent each in first-order logic, defining and using a consistent vocabulary.
- Given the sentence, "All Germans speak the same languages," represent the sentence in predicate calculus.
- Given the blocks-world domain, formalize the domain using the situation calculus.
Reading:Chapter 8 of AIMA Supplemental:Assignment:Homework 3 (middle third): Exercises 8.2, 8.6, 8.7, 8.16 Items Due:No items due, but the second part of Homework 3 has been assigned.

Details:Week 7Topic:Logic and Reasoning: Inference in First-Order Logic Objectives:

- Discuss how to use resolution to show that a sentence is valid or unsatisfiable
- Discuss forward chaining in Propositional and First-Order Logic
- Discuss backward chaining in Propositional and First-Order Logic
Reading:Chapter 9 of AIMA Supplemental:Assignment:Homework 3 (last third): Exercises 9.4, 9.5, 9.19 (a,b,c,d,e only) Items Due:Homework 3

Details:Week 8Topic:Midterm Exam: See Syllabus for policy and schedule

Details:Week 9Topic:Knowledge Representation Objectives:

- Describe the concept of Semantic Network
Reading:Section 10.5, 10.6 of AIMA Supplemental:Assignment:Homework 4 (Part 1): Exercise 10.17 Items Due:No items due this week

Details:Week 10Topic:Planning Objectives:

- Use the STRIPS language to represent steps in a plan
- Explain the relationships among POP, Planning Graphs, and GRAPHPLAN
- What do "STRIPS" and "POP" stand for anyway?
- Criticise the statement: planning = search + logic
Reading:Chapter 11, 12 (skim only) of AIMA Supplemental:Assignment:Homework 4 (Part 2): Exercise 11.4, 11.12 Items Due:No items due this week

Details:Week 11Topic:Reasoning under Uncertainty Objectives:

- Understand basic probability, including Bayes Rule and the Product Rule
- State the Kolmogorov Axioms
- State the Product Rule
- State Bayes' Rule, and derive it from the Product Rule
- Describe Bayesian Network
Reading:Chapter 13, 14 (Bayesian Networks) of AIMA Supplemental:Assignment:Homework 4 (Part 3): Exercises 13.2, 13.4, 14.1 (parts a, b, c only) Items Due:Homework 4

Details:Week 12Topic:Making Decisions Objectives:

- Define or state:

- The
expected utilityof an action- The principle of
Maximum Expected Utility(MEU)Rational behaviorin terms of MEU- The
axioms of utility theory- Explain how the axioms of utility theory imply the existence of a utility finction
- Set up and evaluate a decision network for a given decision problem
- Describe informally how information is valued in a decision environment
Reading:Chapter 16 of AIMA (skim) Supplemental:Assignment:Homework 5 (Part 1): (empty) Items Due:No items due this week

Details:Week 13Topic:Machine Learning Objectives:

- Describe the general learning model. Given a common human learning environment (infant learning a language, adult learning to drive), explain how it fits into the general learning model, identifying components of the model as appropriate.
- Given a learning algorithm and a sample domain, implement the algorithm and assess its operation.
- Describe the decision tree learning algorithm
Reading:Chapter 18 of AIMA Supplemental:Assignment:Homework 5 (Part 2): 18.1, 18.3, 18.4 Items Due:No items due this week

Details:Week 14Topic:Nearest Neighbor and Neural Network Learning Objectives:

- Describe and implement the
k-nearest neighbor learning algorithm- Trace the perceptron learning algorithm
- Construct a 2-layer neural network that computes a given binary logic function
Reading:Sections 20.4, 20.5 of AIMA Supplemental:Assignment:Homework 5 (Part 3): 20.11 Items Due:Homework 5

Details:Week 15Topic:Stepping Back Objectives:

- Contrast the concepts
weak AIandstrong AI- Discuss is the
mind-body problemand associateddualistandmonisttheories- Discuss 6 potential threats to society posed by AI and related technology.
- Discuss the potential good / risk of AI for the future in terms of the question:
Should AI progress be encouraged?Reading:Chapters 26, 27 of AIMA Supplemental:Assignment:Spend some time contemplating your understanding of and views toward AI, before and after this course. Items Due:No items due this week

Details:Week 16Topic:Final Exam: See Syllabus for policy and schedule

**Blackboard Dropbox Submission Process:**

Assignments should be submitted via the Drop Box on the course web site in Blackboard no later than 11:59:59 pm on the deadline day. The time stamp placed there by the receiving server will be the determining factor. (It is currently using Eastern time.)

Note the distinction between uploading file to the dropbox and actually submitting the files. Files that are uploaded but not submitted will still have the "remove" option displayed. Such files are not visible to the instructors.

Files should be of either text or pdf format. File names should be in the form

<id>hw<nn>[<clarifier>]where<id>is your Blackboard login name,<nn>is a digit for the number of the assignment, and[<clarifier>]is an optional tag to further identify a file. The appropriate suffix indicating the file type should follow the name.Example file name:

abc03hw2.txt- Homework Assignment 2 submitted byabc03in text format.