CS60045 Artificial Intelligence | Autumn 2022, L-T-P: 3-0-0 |
Schedule
Instructors Prof. Pallab Dasgupta
Prof. Partha Pratim ChakrabartiTiming WED (10:00 AM – 10:55 AM), THU (9:00 AM –9:55 AM), FRI (11:00 AM –11:55 PM) Venue Room No: NR-421, Nalanda Academic Complex Team Code 732ru1m Teaching Assistants 1. Briti Gangopadhyay (briti_gangopadhyay@iitkgp.ac.in),
2. Sumanta Dey (sumanta.dey@iitkgp.ac.in),
3. Ajinkya Waghmare (waghmareaju1216@gmail.com),
4. Somesh Kishor Kharat (somesh3199@kgpian.iitkgp.ac.in),
5. Debjyoti Das Adhikari (debjyoti.das.adhikary@gmail.com)
6. Aayush Prasad (aayuprasad@iitkgp.ac.in)
7. Maj Rakshit Sharma
8. Naincy Vimal (naincyvimal2109@kgpian.iitkgp.ac.in)
Announcements
1. Marks distribution:
- Class Test: 10%
- Mid Sem: 30%
- Project: 15%
- End Sem: 40%
- Attendance: 5%
2. Class Test 1 on 2nd September at 11:00 AM - 12:55 PM Syllabus
Introduction Course Introduction, Motivation. [1 hour] Problem solving by search State Space, Problem Reduction, Game Playing, Constraint Satisfaction. [7 hours] Automated Reasoning Proposition and first order logic, inference and deduction, resolution refutation, answer extraction, knowledge based systems, logic programming and constrained logic programming, non-monotonic reasoning. [6 hours] Planning State-space, plan space and partial order planning, planning algorithms. [4 hours] Reasoning under uncertainty Probabilistic reasoning, belief networks [5 hours] Learning Inductive learning, decision trees, logical approaches, computational learning theory, neural networks, reinforcement learning, Intelligent agents, natural language understanding, Applications. [8 hours] Books and References
[1] Stuart Russell, Peter Norvig, Artificial intelligence : A Modern Approach, Prentice Hall, Fourth edition, 2020. [2] Nils J. Nilsson, Artificial Intelligence: A New Synthesis, Morgan-Kaufmann, 1998. [3] Judea Pearl, Heuristics: Intelligent Search Strategies for Computer Problem Solving, Addison-Wesley Publishing Company, 1984. [4] Biere, A., Heule, M., Van Maaren, H., Walsh, T., Handbook of Satisfiability, IOS Press, 2009. Classes Material
Week Topic Chapter Annotated PDF Video Link Tutorial Week 1 Introduction Introduction Link - Link - Automated Problem Solving Automated Problem Solving Link Link Link - State Space Search Link Link Link - Week 2 Heuristic Search Link Link Link - Heuristic Search Game Trees Link Link Link - Week 3 Game Trees Holiday 1 - - - - Holiday 2 - - - - Week 4 Local Search Link - Link - Propositional Logic Propositional Logic Link Link Link - Propositional Logic to Predicate Logic Link Link Link - Week 5 Predicate Logic Fundamentals Link Link Link - Resolution Refutation Link Link Link - Class Test 1 - - - - Week 6 Propositional Logic Resolution Refutation Link Link Link - Constraint Satisfaction Problems Link Link Link - Planning in AI Planning in AI Part 1 Link Link Link - Week 7 Planning in AI Part 2 Link Link Link - Planning in AI Part 3 Link Link Link - Tutorials - - - Questions
SolutionsWeek 8 Reasoning Under Uncertainty Part 1 Link Link Link - Part 2 Link Link - Tutorial (CSP, Bayes Net, Graph Plan) Link - Answers Week 9 Machine Learning Machine Learning Fundamentals Link - Link - Learning Decision Trees Link - Link - Week 10 Neural Networks Link - Link - Deep Learning Fundamentals Link - Link - Week 10 Reinforcement Learning Fundamentals Link - Link - Previous course pages: 2021 | 2020 | 2019 | 2018
CS60045 Artificial Intelligence | Autumn 2022, L-T-P: 3-0-0 |