Diploma in Artificial Intelligence

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    Mode Of Examination

    Online Examination

    Number Of Question: 100 (1 Marks Each)

    Total Time: 120 Min

    Syllabus

    Introduction to Artificial Intelligence:

    History, linguistics, facts and agents of artificial-intelligence.

    Intelligent Agents:

    Various aspects of intelligent agents like their architecture and environments.

    Problem Solving:

    Different approaches to problem solving like uninformed and informed search strategies, local search and optimization problems and other constraints satisfaction problems.

    Adversarial Search:

    Approaches to game theory problems like state space search and alpha beta pruning.

    Logical Agents:

    Agents that reason logically, first order logic and the inference in first order logic which includes forward and backward reasoning.

    Knowledge and Reasoning:

    Inference in first order logic, rule based system, semantic net, frames, unification and lifting.

    Planning and Acting in the Real World:

    Different types of planning like partial order planning, graph planning and real world planning.

    Uncertain Knowledge and Reasoning:

    Uncertainty, probability notations and bayesian networks and various probabilistic reasoning systems. Hidden markov models, expert systems, Uncertain reasoning also includes semantic representation and object recognition.

    Learning:

    Learning from observations which includes decision trees, learning in neural and belief networks, reinforcement learning and knowledge in learning. It includes questions on inductive logic programming.

    Communicating, Perceiving and Acting:

    The agents that communicate which includes robotics, practical natural language processing and perceptions.

    LISP Programming:

    LISP programming.

    AI Algorithms & Statistics:

    Various other topics of artificial-intelligence, ai algorithms and statistics.

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