EC36: Eletive-VIII Syllabus for EL 6th Sem 2017 DBATU

Eletive-VIII detailed syllabus scheme for B.Tech Electronics Engineering (EL), 2017 onwards has been taken from the DBATU official website and presented for the Bachelor of Technology students. For Subject Code, Course Title, Lecutres, Tutorials, Practice, Credits, and other information, do visit full semester subjects post given below.

For all other DBATU Syllabus for Electronics Engineering 6th Sem 2017, do visit EL 6th Sem 2017 Onwards Scheme. The detailed syllabus scheme for eletive-viii is as follows.

Eletive-VIII Syllabus for Electronics Engineering (EL) 3rd Year 6th Sem 2017 DBATU

Course Objectives:

For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
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Course Outcomes:

After successfully completing the course students will be able to

1. Design and implement key components of intelligent agents and expert systems.
2. To apply knowledge representation techniques and problem solving strategies to common AI applications.
3. Apply and integrate various artificial intelligence techniques in intelligent system development as well as understand the importance of maintaining intelligent systems.
4. Build rule-based and other knowledge-intensive problem solvers.

Unit 1

Foundation
Intelligent Agents, Agents and environments, Good behavior, The nature of environments, structure of agents, Problem Solving, problem solving agents, example problems, Searching for solutions, uniformed search strategies, avoiding repeated states, searching with partial information.

Unit 2

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Unit 3

Knowledge Representation
First order logic, representation revisited, Syntax and semantics for first order logic, Using first order logic, Knowledge engineering in first order logic, Inference in First order logic, prepositional versus first order logic, unification and lifting, forward chaining, backward chaining, Resolution, Knowledge representation, Ontological Engineering, Categories and objects, Actions – Simulation and events, Mental events and mental objects.

Unit 4

Learning
Learning from observations: forms of learning, Inductive learning, Learning decision trees, Ensemble learning, Knowledge in learning, Logical formulation of learning, Explanation based learning, Learning using relevant information, Inductive logic programming, Statistical learning methods, Learning with complete data, Learning with hidden variable, EM algorithm, Instance based learning, Neural networks – Reinforcement learning, Passive reinforcement learning, Active reinforcement learning, Generalization in reinforcement learning.

Unit 5

For the complete syllabus, results, class timetable, and many other features kindly download the iStudy App
It is a lightweight, easy to use, no images, and no pdf platform to make students’s lives easier.
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Unit 6

Natural Language Understanding
Why NL, Formal grammar for a fragment of English, Syntactic analysis, Augmented grammars, Semantic interpretation, Ambiguity and disambiguation, Discourse understanding, Grammar induction, Probabilistic language processing, Probabilistic language models.

Reference/Text Book:

1. Stuart Russell, Peter Norvig, Artificial Intelligence, A Modern Approach, Pearson Education/Prentice Hall of India.
2. Elaine Rich and Kevin Knight, Artificial Intelligence, Tata McGraw-Hill.
3. Nils J. Nilsson, Artificial Intelligence: A new Synthesis, Harcourt Asia Pvt. Ltd.
4. George F. Luger, Artificial Intelligence-Structures and Strategies for Complex Problem Solving, Pearson Education/ PHI.

For detail syllabus of all other subjects of Electronics Engineering (EL) 6th Sem 2017 regulation, visit EL 6th Sem Subjects syllabus for 2017 regulation.