CSCE 420: Introduction to Artificial Intelligence
Instructor: Dr. Dylan Shell.
|Office hours||:||Mondays, 11:30am-12:30pm and by appointment too.|
|Office hours||:||Fridays 3pm-4pm.|
|Lecture Time||:||Tuesdays and Thursdays, 11:10am-12:25pm.|
|Lecture Location||:||HRBB 113|
Fundamental concepts and techniques of intelligent systems; representation and interpretation of knowledge on a computer; search strategies and control; active research areas and applications such as notational systems, natural language understanding, vision systems, planning algorithms, intelligent agents and expert systems.
The course is a broad survey that will require a significant amount of reading with simple introductory programming in different languages. It will provide an understanding of the state of the practice of AI and set the foundation for further study in agency, fuzzy logic, neural networks, robotics, uncertainty, and computer vision.
A class on Design and Analysis of Algorithms (which will likely have a course on Data Structures and Algorithms, and Programming Studio as prerequisites).
Learning Outcomes or Course Objectives
- List the basic techniques for creating intelligent programs. This will be measured by quizzes, and tests.
- Create a successful program illustrating the operation of one of these methods. This will be measured by the programming assignments.
- Apply the right programming language or technique to the right problem and be able to evaluate a proposed AI application for likelihood of success. This will be measured by programming assignments.
- Be able to discern sensationalism from science on the possible impact of AI on society. This will be measured by the final.
Artificial Intelligence: A Modern Approach 3rd Edition by Stuart Russell and Peter Norvig, 2009.
- [CMI] "Computing Machinery and Intelligence," by Alan M. Turing. Mind 49:433-460, 1950.
- [D*Lite] "D* Lite," by S. Koenig and M. Likhachev. Proceedings of the AAAI Conference of Artificial Intelligence (AAAI), 476-483, 2002
- [E-Graphs] "E-Graphs: Bootstrapping Planning with Experience Graphs," by Mike Phillips, Benjamin Cohen, Sachin Chitta and Maxim Likhachev. Proceedings of the Robotics: Science and Systems Conference, 2012.
- [Do-Calc] "Introduction to Judea Pearl's Do-Calculus," by Robert R. Tucci, Apr 2013.
- [IwoR] "Intelligence without representation," by Rodney A. Brooks, 1991.
- [POMDP] Tony Cassandra's POMDP Tutorial
- [SoA] The Sciences of the Artificial, 3rd Edition by Herbert A. Simon, 1996.
Here are some other materials that are useful.
- The Dartmouth Conference Proposal
- Terry Bisson's "They're made out of meat"
- The R&N map of Romania 2
- BBC Radio 4: Melvyn Bragg's discussion of the history and overview of logic
- A good example of how to communicate a technical topic in an engaging way: Hexaflexagons
- A previous communication projects: 1 2 3
- Luciano Floridi on Singularitarians, AItheists, etc.
- Michael Jordan on the delusions of big data
- Magenta and how we perceive colour
Communications Projects (a selection)
Here are some of this year's highlights!
- F.E.A.R. Game AI (Joanne Bruno and Sara Fox)
- Iterative Deepening (Timothy Foster, Evan Feiereisel, Zander Kelley, and Nafe Alsawfta)
- Automatic Speech Recognition with Hidden Markov Models (Hira Chaudhary)
- AI in Mobile Systems (Angel Lozano)
- How does a computer play chess? (Kevin Shell)
- Navigation in Realtime Strategy Games (Garrett Witowski and Kyle Wahl)
- Training your cooking robot (Eric Cochrane)
- Clustering - DBSCAN (Steven Bierwagen)
- Self-Driving Cars (Steven Snow and Chris Martin)
Grades will be based on:
The grading scale is:
Course Topics, Calendar of Activities, Major Assignment Dates
Syllabus topics and readings are subject to change, exact dates depend on class progress.
|1||Introduction, Search||1, 2 & 3.|
|2||Search continued, search for games, etc||3, 4 & 5.|
|6 & 7||Logic: Inference||9.|
|11||Neural networks, reinforcement learning||18.7, 21.1, 21.2.|
|12||Natural language processing||22.|
|We will have approximately one quiz every other week, sometimes one every three weeks. The quiz will cover material that has been previous covered in class. They are all open book.|
|This is an example quiz: Spring 2010, Quiz 1|
|This is an example quiz: Spring 2010, Quiz 2|
|Due Date||Class Tests and Assignments|
|8 Sep||Programming Assignment on Enumerating State Spaces Posted Here [Lisp]|
|22 Sep||Programming Assignment on Search for Games Posted Here|
|29 Sep||Class Test 1|
|6 Oct||Programming Assignment on Search Posted Here|
|20 Oct||Programming Assignment on Prolog Posted Here|
|5 Nov||Class Test 2|
|12 Nov||Programming Assignment on Logical Inference Posted Here|
|19 Nov||Programming Assignment on Planning Posted Here|
|24 Nov||Communication Project Posted Here|
|26-27 Nov||Thanksgiving Holiday|
|3 Dec||Class Test 3|
|8 Dec||Take home final due Final Exam Posted Here|
|Dates in parentheses arn't yet firm, being subject to change.|
Students with Disabilities
The Americans with Disabilities Act (ADA) is a federal anti-discrimination statute that provides comprehensive civil rights protection for persons with disabilities. Among other things, this legislation requires that all students with disabilities be guaranteed a learning environment that provides for reasonable accommodation of their disabilities. If you believe you have a disability requiring an accommodation, please contact Disability Services, in Cain Hall, Room B118, or call 979-845-1637. For additional information visit http://disability.tamu.edu.
Academic IntegrityFor additional information please visit: http://student-rules.tamu.edu/aggiecode
Policy on Missed Work
Material missed due to recognized absences (illness with doctor's excuse, death in the family) can be made up for full credit. Late material is accepted solely at the discretion of the instructor, at least 1 class period's prior notice must be given for consideration of acceptance of late material.