Artificial Intelligence Handwritten Notes
What is Artificial Intelligence (AI) ?
Artificial Intelligence (AI) is a branch of Science which deals with helping machines find solutions to complex problems in a more human-like fashion. This generally involves borrowing characteristics from human intelligence, and applying them as algorithms in a computer friendly way.
What is the Need for Artificial Intelligence ?
To create expert systems which exhibit intelligent behavior with the capability to learn, demonstrate, explain and advice its users. Helping machines find solutions to complex problems like humans do and applying them as algorithms in a computer-friendly manner.
What are the Applications of Artificial Intelligence ?
Applications of AI include Natural Language Processing, Gaming, Speech Recognition, Vision Systems, Healthcare, Automotive etc.
Topics in our Artificial Intelligence Handwritten Lecture Notes PDF
In these “Artificial Intelligence Handwritten Lecture Notes PDF”, you will study the basic concepts and techniques of Artificial Intelligence (AI). The aim of these notes is to introduce intelligent agents and reasoning, heuristic search techniques, game playing, knowledge representation, reasoning with uncertain knowledge.
The topics we will cover will be taken from the following list:
Introduction: Introduction to artificial intelligence, background and applications, Turing test, rational agents, intelligent agents, structure, behaviour and environment of intelligent agents.
Knowledge Representation: Propositional logic, first order predicate logic, resolution principle, unification, semantic nets, conceptual dependencies, frames, scripts, production rules, conceptual graphs.
Reasoning with Uncertain Knowledge: Uncertainty, non-monotonic reasoning, truth maintenance systems, default reasoning and closed world assumption, Introduction to probabilistic reasoning, Bayesian probabilistic inference, introduction to fuzzy sets and fuzzy logic, reasoning using fuzzy logic.
Problem Solving and Searching Techniques: Problem characteristics, production systems, control strategies, breadth first search, depth first search, hill climbing and its variations, heuristics search techniques: best first search, A* algorithm, constraint satisfaction problem, means-end analysis.
Game Playing: introduction to game playing, min-max and alpha-beta pruning algorithms.
Prolog Programming: Introduction to Programming in Logic (PROLOG), Lists, Operators, basic Input and Output.
Understanding Natural Languages: Overview of linguistics, Chomsky hierarchy of grammars, parsing techniques.
Ethics in AI, Fairness in AI, Legal perspective