Instructor  Feng Chen 
Office  UAB426 
Number  (518) 4424270 
fchen5@albany.edu  
Office Hour  Wednesday: 1:00PM to 2:00PM
Thursday: 10:00AM to 11:00AM 
TA  Chunpai Wang

Office  UAB 433 
Number  
cwang25@albany.edu  
Office Hour  Tuesday 12:00PM to 1:00PM
Thursday 12:00PM to 1:00PM 
TA  Erkang Xie

Office  UAB 433 
Number  
exie@albany.edu  
Office Hour  Tuesday 3:00PM to 5:00PM
Thursday 2:30PM to 4:30PM 
TA  Harinder Singh

Office  UAB 433 
Number  
ssingh22@albany.edu  
Office Hour  Monday 1:15PM to 3:15PM
Friday 1:15PM to 3:15PM 
Class Time and Location  Th 5:45PM  8:35PM, HU137 
Class Website  http://www.cs.albany.edu/~fchen/course/ICSI2016535/ 
Course Postings
Course Description:
A first course in artificial intelligence (AI) introducing basic concepts and techniques. Topics include statistics, optimization, first order logic, probabilistic soft logic, Markov model and hidden Markov models, Markov random fields, and Artificial Neural networks.
TextBook
Authors: Stuart Russel and Peter Norvig ISBN10: 9332543518 ISBN13: 9789332543515 Publisher: PE; 3 edition(2015) Textbook Website: http://aima.cs.berkeley.edu/ 
Course Description:
Part  Lecture  Lecture Topics  Notes 
A: Statistics  1  Basic Distribution (Binomial, Poisson, Gaussian)  
2  Parameter Esitmation (Maximum Likelihood Estimation)  
B: Numerical Optimization Techniques  3  Gradient, SubGradient Gradient Descent, Project Gradient Descent 

4  Parallel Algorithms (The alternating direction method of multipliers)  
C: First Order Logic  5  Syntax and Semantics Learning and Inference 

D: Probablistic Soft Logic  6  Syntax and Semantics Learning and Inference 

E: Markov Model and Hidden Markov Model  7  TBD 

F: Markov Random Fields  8  TBD 

9  TBD 

G: Artificial Neural Networks  10  TBD 

11  TBD 
Examinations and Grading:
Homework
Course Project Requirement
Course Project teams:
to be announced
Policy on Cheating:
Cheating in an exam will result in an E grade for the course. Further, the students involved will be referred to the Dean's oce for disciplinary action.
Homework problems are meant to be individual exercises; you must do these by yourself. Any of the following actions will be considered as cheating.
Cheating in a homework exercise will result in the following penalty for all the students involved.
Students who cheat in two or more homeworks will receive an E grade for the course. The names of such students will also be forwarded to the Dean's oce for disciplinary action.