Cs 4408 Artificial Intelligence

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Course Outline

CS 4408: Artificial Intelligence

Prerequisites:

MATH1302: Discrete Mathematics, CS3304: Analysis of Algorithms, CS4402: Programming Languages, and CS4407: Machine Learning.

Course Description:

This course is an introduction to artificial intelligence. The course will cover the history, theory, and computational methods of artificial intelligence. Basic concepts will examine agents in the context of computational intelligence. The course will also explore representations of knowledge, search as a problem solving technique, reasoning with both certainty and uncertainty and the resulting role of probability when reasoning in uncertainty. The course will also address planning concepts and the role of multi-agent systems.

Required Textbook and Materials:

The main required textbooks for this course are listed below, and can be readily accessed using the provided links. There may be additional required/recommended readings, supplemental materials, or other resources and websites necessary for lessons; these will be provided for you in the course’s General Information and Forums area, and throughout the term via the weekly course Unit areas and the Learning Guides.

Poole, D. L., & Mackworth, A. K. (2010). Artificial Intelligence: foundations of computational agents. Cambridge University Press. Available online at http://artint.info/. The textbook is published by Cambridge University Press, 2010. The complete text and figures of the book are here, copyright David Poole and Alan Mackworth, 2010. The HTML is made available under a Creative Commons Attribution-Noncommercial-No Derivative Works 2.5 Canada License.

Additional readings will be assigned within specific units.
Software Requirements/Installation: Throughout this course we will be putting our skills into practice by completing the exercises in the AISpace.org web site. In some cases your instructor will provide ADDITIONAL INSTRUCTIONS that you must incorporate into the exercise.

The exercises all take advantage of Java applets. You have the option of installing java and ensuring that your web browser can execute the applets .

Learning Objectives and Outcomes:

By the end of this course students will be able to:

  1. Define artificial intelligence and its characteristics.
  2. Describe both the Turing Test and the Chinese Room as tests of intelligence.
  3. Define the structure, types, characteristics, and behaviors of agents.
  4. Demonstrate familiarity with search algorithms as a problem solving strategy
  5. Demonstrate familiarity with constraint satisfaction problems (CSP).
  6. Demonstrate familiarity with Knowledge representation and reasoning concepts including propositional and predicate logic.
  7. Explain the role and application of probability in reasoning.
  8. Define approaches to planning both with certainty and uncertainty.

Course Schedule and Topics: This course will cover the following topics in eight learning sessions, with one Unit per week. The Final Exam will take place during Week/Unit 9.

Week 1: Unit 1 – Fundamentals of AI

Week 2: Unit 2 – Agents

Week 3: Unit 3 – Problem Solving Through Search

Week 4: Unit 4 – Features and Constraints

Week 5: Unit 5 – Knowledge Representation and Reasoning

Week 6: Unit 6 – Reasoning Under Uncertainty

Week 7: Unit 7 – Planning

Week 8: Unit 8 – Multi-Agent Systems

Week 9: Unit 9 – Course Review and Final Exam