Artificial Intelligence & Soft Computing Laboratory
Subject Overview
The practical companion to Artificial Intelligence & Soft Computing, implementing logic programming, search techniques, text processing, perceptron and associative network training, backpropagation, fuzzy set operations, and a genetic algorithm optimization in MATLAB/Python. A 2-credit elective lab paper.
Unit-wise Syllabus
1 units — click WhatsApp below to get the full notes for each
Unit 1: AI and soft computing implementation
Logic programming for prime numbers and family tree relationships, puzzle solver, uninformed and heuristic search implementation, text tokenization and Bag-of-Words frequency extraction, text category prediction, audio signal visualization and generation, perceptron training with fixed increment learning, ADALINE/MADALINE AND function implementation, auto-associative and hetero-associative networks via HEBB and outer product rules, backpropagation network for 3 epochs, fuzzy set operations (union, intersection, complement, difference) and max-min composition, genetic algorithm function maximization over 6 iterations