TA Matrerials
Coms 572:
Princinples in Artifical Intelligence
Fall 2002
TA for Coms 572:
Princinples in Artifical Intelligence, Iowa State University, Fall 2002 (from 2002-08-26)
Howe 1304, TA office Atanasoff B09 (B23 before Sept 23) , I'm TA for this course
Materials for students:
- Homework 1 (about AI basic cocept, agent definition and uninformed search)
Out: Sept. 4, 2002.
Due: Sept. 20, 2002
- Paper required to Read: A. Turing, Mind, 1950
- Some hints (Given in Help Session Sept 9 & Sept 16)
- Solution (by Dr. Margaritis)
- Laboratory Project 1 (about DFS, BFS and informed search)
Out: September 18, 2002,
Due: October 7, 2002
- Hints 1 (given in Help Session Sept 23, 2002)
- Hints 2 (given in Help Session Sept 20, 2002)
- The zipped intranet to test your program (78k)
- Homework2 (about informed search and Constraint Satisfaction Problem) Out: Sept. 25, 2002. Due: Oct. 14, 2002
- Midterm Help (Oct 25, 2002)
- Hints for sample Mid-term
- Hints for Exercises of chapter 6
- Solution (Oct 27, 2002)
- Homework3 (about logic & probability)[ PDF | PS ]. Out: Oct. 28, 2002. Due: Nov. 11, 2002
- Laboratory Project 2 (about Decision Tree) Out: November 11, 2002, Due: December 2, 2002
- Homework 4 (about Beyesian Learning and Nerual Network)[ PDF | PS ].
Out: Nov. 30, 2002.
Due: No due time
- Solution
(Given on Dec 7 2002)
- Solution
(Given on Dec 7 2002)
- Final Help
- Java Language
- A simple but useful tutorial for Java: Java for C++ Programmers
- Document for JDK (1.4.1)
- Java help in MSDN (Microsoft J++ and J#)
- A good and small java IDE : JCreator (It's based on JDK)
- The text: Artificial Intelligence: A Modern Approach, ( AIMA), Stuart Russell and Peter Norvig
- From Kansas State University, Dept of Computing and Information Sciences, CIS730 course <-
- From Saga University, Department of Information Science, Intelligent Systems
- From University of California@Berkeley, Computer Science Division, CS 188
- Other Information:
- Try to find resources from those who also use this book! (problemset, exam, code, idea...) <-
- Code for the text
- Lisp: Downloading and Installation | Overview
- Python: preliminary version
- C++: (L. Holder) Course | Code File
- Prolog: (L. Holder) Course | Code File
- Java: (D. Harada) preliminary version
- Some other useful code:
- Agent infrastructure
- Voyager : frame for mobile agent
- WEKA : package for machine learning
- Zeus Agent System
- Search algorithms
- First Order Logic
- Bayesian
- Neural Network
- Agent infrastructure
Some slides for this book. It's much easier to read slides than to read that voluminous & verbose brick....