Announcements Syllabus Homework Projects Paper Useful Links Slides

- A listing of and links to all final papers are now available
- Midterm #2: The midterm is scheduled for Thursday December 13th from 10am-12pm. It will be in our regular room. Sample Homework available here. One notecard 3x5 will be allowed. Here is a template for those that want.
- ALL Students: Term paper is due on Thursday November 29th. Please email the digital copy to your instructor and TA. Also, turn in a hard copy in class (two-sided please).
- ALL Students: Programming assignment 1 is due on
~~November 8th~~extended to Nov 13th. - ALL Students: Paper topics are due by midnight Wed. October 31st. Students who have not sent their paper topics.
- ALL Students: Exam 1 will be on Tues. Oct 23rd. A list of topics is available here. We will talk about the exam topics on Thursday the 18th. One notecard 3x5 will be allowed. Here is a template for those that want.
- ALL Students: Homework 5 is due Thurs. Oct 4th.
- ALL Students: Homework 4 is due Thurs. Sept 27th.
- ALL Students: Homework 3 is due Tues. Sept 18th.
- TA office hours have been moved to Thurs. 11am-12pm.
- ALL Students: Homework 2 is due
~~Tues. Sept 4th~~. Extended to Thurs. Sept. 6th - We have a new classroom! We will be in SARA RAYNOLDS HALL (SARAR) 101 starting on Tuesday, 8/28.
- ALL Students: Homework 1 is due Thurs. August 23rd.

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Office Hours: Tues. 2:00-4:00 and Wed. 2:00-3:00; other times by appointment

Email: tapia@cs.unm.edu

Office Phone: 505-277-0858

Office: 126

Office Hours: Monday 3:00-5:00pm and Thursday 11:00am-12:00pm; other times by appointment

Email: pdevineni@cs.unm.edu

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Week of | Topic | Reading |
---|---|---|

8/21 | AI, its roots and scope | Ch 1 |

8/28 | The Predicate Calculus | Ch 2 |

9/4 | Structures and strategies for state space search | Ch 3 |

9/11 | Heuristic search | Ch 4 |

9/18 | Probabilistic Methods in AI | Ch 5 |

9/25 | Architectures for AI problem solving | Ch 6 |

10/2 | Prolog | N/A |

10/9 | Intro. AI representational Schemes | Ch 7 |

10/16 | Representation & knowledge-based systems | Ch 8 |

10/23 | Representation & knowledge-based systems | Ch 8 |

10/30 | Reasoning in uncertain situations | Ch 9 |

11/6 | Building a rule based expert system in Prolog | N/A |

11/13 | Building a rule based expert system in Prolog | N/A |

11/20 | Advanced topic: Robotic Intelligence | N/A |

11/27 | Advanced topic: Robotic Intelligence | N/A |

11/4 | Course Summary and review | Ch 16 |

Your grade will be based on four components:

- exams 40% There will be two midterm exams, worth 20% each
- homework 20% There will be 10 weekly assignments, typically due every Tuesday.
- programs 25% There will be 2-3 programming projects. More details are available here.
- paper 10% There will be a 5-10 page paper, on a topic in AI of the student's choice. More details are available here.
- participation 5% We will define participation during this course. Options will include: industry speakers, attendance, etc.

A for 90% or above of the total points,

B for 80 to 89%,

C for 70 to 79%,

D for 60 to 69%,

and F for less than 60%.

For the assignments in this class, discussion of concepts with others is encouraged, but

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Due: 12:30pm on Tuesday, Sept 18th.

(1) Textbook page 162, #6, Heuristic Comparision. (2) Textbook page 163, #13, Minimax execution. (3) Textbook page 164, #14, Alpha-beta pruning. Due: 12:30pm on Thursday, Sept. 27th,

(1) Textbook page 192, #14, Manufacturing a product. (2) Textbook page 192, #16, Automobile insurance company. (3) Textbook page 192, #17, Prisoner probabilities. Due: 12:30pm on Thursday, Oct. 4th.

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- Building graph search algorithms in Prolog and another language a) depth-first b) breadth-first c) best-first search d) A* search
- Using EXSHELL, Lispshell, or JESS to build a rule-based expert reasoning system
- Creating a natural language parser in Prolog

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Specific details for CS 427:

- Papers should be at least 5 pages in length.
- Papers should have at least 5 technical citations (not wikipedia, websites, etc.).

- Students should pick a topic realated to their research interests.
- Papers should be at least 10 pages in length.
- Papers should have at least 10 technical citations (not wikipedia, websites, etc.).

- A specific game solved with AI techniques, e.g., tic-tac-toe, mastermind, chess, Mario AI, etc.
- A specific technique in AI, e.g., heuristic search, Bayes' theorem, etc.
- A general topic in AI, e.g., natural language parsers, cortical networks, etc.
- An implementation of an AI method. However, please include an appropriate literature review.

- The Turing Award Lecture by Judea Pearl titled "The Mechanization of Causal Inference: A 'Mini Turing Test' and Beyond."
- Book Website
- Chapter 1 of course textbook
- Free Software Prolog Compiler

- Lecture 1 -- Predicate Calculus
- Lecture 2 -- Uninformed Search
- Lecture 3 -- Informed Search
- Lecture 4 -- Stochastic Methods
- Lecture 5 -- Production Systems
- Lecture 6 -- Motion Planning
- Lecture 7 (part 1) -- Knowledge Representation
- Lecture 7 (part 2) -- Knowledge Representation
- Lecture 8 -- Strong Methods
- Lecture 9 -- Nearest Neighbor/Decision Tree
- Lecture 10 -- Uncertainty
- Reinforcement Learning

Announcements Syllabus Homework Projects Paper Useful Links Slides