PROFESSIONAL ELECTIVES

Electives in Artificial Intelligence

Unit I

AI in decision making, Qualitative reasoning, Formal concepts and relation, views and phenomena, deriving and reasoning with HPT model, essential features of control systems, concerning time and correct functioning of systems, Q-Model.

Unit II

Intelligent control system, control system development, phase space navigator, stabilizing, architecture for intelligent control systems, multiresolution control architecture (MCA), MCA in autonomous control system, algorithm for MCA, Complexity of knowledge representation and manipulation.

Unit III

DAI techniques in manufacturing control, Distributed AI, VerFlex, Neurocontrol architectures, robot neurocontrol, NN based adaptive controller, case study

Course Outcomes

CO1: Identify the potential use of AI in industrial automation.

CO2: Elucidate the need and implementation of intelligent control systems.

CO3: Understand the components of multiresolution control architecture.

CO4: Learn the methods for solving industrial problems using distributed artificial intelligence.

CO5: Understand the ethics and standards of industrial decision making through case studies.

CO-PO Mapping

Evaluation Pattern: 70:30

*CAT – Can be Quizzes, Assignments, and Reports

*CAL – Can be Lab Assessments, Project, and Report

**End Semester can be theory examination/ lab-based examination/ project presentation

Textbook(s)

Bhaskar Ghosh, Rajendra Prasad, Gayathri Pallail, “The Automation Advantage: Embrace the Future of Productivity and Improve Speed, Quality, and Customer Experience Through AI”, ‎ McGraw Hill,2022.

Spyros G. Tzafestas, Henk B. Verbruggen, “Artificial Intelligence in Industrial Decision Making, Control and Automation”, Springer Dordrecht, 1995.

Reference(s)

Yadav, Satya Prakash, Dharmendra Prasad Mahato, and Nguyen Thi Dieu Linh, eds. “Distributed artificial intelligence: A modern approach”. CRC Press, 2020.

Pascal Bornet, “INTELLIGENT AUTOMATION: Learn how to harness Artificial Intelligence to boost business & make our world more human”, 2020.

Tom Taulli, “The Robotic Process Automation Handbook: A Guide to Implementing RPA Systems”, Apress, 2020.

Berrah, Lamia, and Damien Trentesaux. “Decision-Making in Future Industrial Systems: Is Ethics a New Performance Indicator?.” Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future: Proceedings of SOHOMA 2020. Springer International Publishing, 2021.