The use of computers to solve complex problems is the fundamental theme of Artificial Intelligence. The notion of intelligence being captured by problem solving ability reflects throughout the course. Understanding the difficult problems in computation and interpreting software as intelligent agents is important. Modeling the problems in a way that can be solved using computer programs is very crucial to understanding artificial intelligence.

About the Institute

Indian Institute of Information Technology Vadodara was established in 2013 under Public Private Partnership of Government of India, Government of Gujarat, Tata Consultancy Services, Gujarat State Fertilizer Company and Gujarat Energy Research and Management Institute. Further, the institute has been declared as an Institute of National Importance by an Act of Parliament. The major objective of its establishment is to set up a model of education which can produce best-in-class human resources in IT and harnessing the multidimensional facets of IT in various domains.

Programme Objectives

After undergoing this course, the students will be able to design and develop programs for an agent to learn and act in a structured environment. The course aims at introducing the fundamental aspects of state space search and game playing agents. The other major aspect covered in the course is about classification problems, i.e. both generative and discriminative models.

Laboratory

The course has a very strong laboratory component based on Python, R and Matlab. For a better learning experience participants should install R and/or Octave/Matlab if possible on their computer. Participants will be provided with the list of libraries and work folder containing all the codes prior to the hands-on/laboratory sessions.

Course Contents

State Space Search: Heuristic Search, Best First Search, Hill Climbing, A*,

Beyond Classical Search: Simulated Annealing, Genetic Algorithm, Google PageRank

Adversarial Search: Two player games, Min-Max and Alpha-Beta pruning

Discriminative Models: Classification and Regression Tree, Random Forest, Neural Network, Support Vector Machine

Workshop Chair

Experts