You should properly use the provided pdf book to score well in exams. There is a proper procedure to be followed to achieve success through this PDF. Get the printout of the notes and read it thoroughly. Read the chapters and highlight the important topics.
Revise the topics thoroughly and understand them perfectly. After reading and learning, study the practice papers and illustrations. There are nine subjects in total out of which there are 5 compulsory subjects. English, Hindi, maths, social science, and science. You get the option to choose for artificial. Students can access the pdf for free.
This book focuses on the fields of hybrid intelligent systems based on fuzzy systems, neural networks, bio-inspired algorithms and time series. This book describes the construction of ensembles of Interval Type-2 Fuzzy Neural Networks models and the optimization of their fuzzy integrators with bio-inspired algorithms for time series prediction. Interval type-2 and type-1 fuzzy systems are used to integrate the outputs of the Ensemble of Interval Type-2 Fuzzy Neural Network models.
Genetic Algorithms. This book provides comprehensive introduction to a consortium of technologies underlying soft computing. The constituent technologies discussed comprise neural networks, fuzzy logic, genetic algorithms, and a number of hybrid systems which include classes such as neuro-fuzzy, fuzzy-genetic, and neuro-genetic systems. This book discusses and combines insights from a remarkably wide range of sources such as Buddhist philosophy, cognitive science, ethology, theoretical biology, and more recent AI research.
This generally involves borrowing characteristics from human intelligence and applying them as algorithms in a computer-friendly way. A more or less flexible or efficient approach can be taken depending on the requirements established, which influences how artificial intelligent behavior appears, Artificial intelligence can be viewed from a variety of perspectives.
To have basic proficiency in a traditional AI language including an ability to write simply to intermediate programs and an ability to understand code written in that language. To have an understanding of the basic issues of knowledge representation and blind and heuristic search, as well as an understanding of other topics such as minimax, resolution, etc. Basic understanding of some of the more advanced topics of AI such as learning, natural language processing, agents and robotics, expert systems, and planning.
Introduction to artificial intelligence: Introduction , history, intelligent systems, foundations of AI, applications, tic-tac-tie game playing, development of ai languages, current trends in AI. Logic concepts: Introduction, propositional calculus, proportional logic, natural deduction system, axiomatic system, semantic tableau system in proportional logic, resolution refutation in proportional logic, predicate logic.
Knowledge representation: Introduction, approaches to knowledge representation, knowledge representation using the semantic network, extended semantic networks for KR, knowledge representation using frames advanced knowledge representation techniques: Introduction, conceptual dependency theory, script structure, cyc theory, case grammars, semantic web.
Expert system and applications: Introduction phases in building expert systems, expert system versus traditional systems, rule-based expert systems blackboard systems truth maintenance systems, application of expert systems, list of shells and tools.
Uncertainty measure: probability theory: Introduction, probability theory, Bayesian belief networks, certainty factor theory, dempster-shafer theory Fuzzy sets and fuzzy logic: Introduction, fuzzy sets, fuzzy set operations, types of membership functions, multi valued logic, fuzzy logic, linguistic variables and hedges, fuzzy propositions, inference rules for fuzzy propositions, fuzzy systems. Any University student can download given B. For any query regarding on Artificial Intelligence Pdf Contact us via the comment box below.
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