Ans: Artificial Intelligence is an area of computer science that emphasizes the creation of intelligent machine that work and reacts like humans.
Ans: Strong AI makes the bold claim that computers can be made to think on a level (at least) equal to humans. Weak AI simply states that some "thinking-like" features can be added to computers to make them more useful tools... and this has already started to happen (witness expert systems, drive-by-wire cars and speech recognition software). What does 'think' and 'thinking-like' mean? That's a matter of much debate.
Ans: Artificial intelligence Neural Networks can model mathematically the way biological brain works, allowing the machine to think and learn the same way the humans do- making them capable of recognizing things like speech, objects and animals like we do.
Ans: Artificial Intelligence can be used in many areas like Computing, Speech recognition, Bio-informatics, Humanoid robot, Computer software, Space and Aeronautics’ etc.
Ans: A top-down parser begins by hypothesizing a sentence and successively predicting lower level constituents until individual pre-terminal symbols are written.
Ans: Georg Thimm maintains a webpage that lets you search for upcoming or past conferences in a variety of AI disciplines.
Ans: Perl language is not commonly used programming language for AI
Ans: In AI, Prolog is a programming language based on logic.
Ans: Strong AI makes strong claims that computers can be made to think on a level equal to humans while weak AI simply predicts that some features that are resembling to human intelligence can be incorporated to computer to make it more useful tools.
Ans: Artificial Intelligence can be used in many areas like Computing, Speech recognition, Bio-informatics, Humanoid robot, Computer software, Space and Aeronautics’ etc.
Ans: Perl language is not commonly used programming language for AI
Ans: Statistical AI is more concerned with “inductive” thought like given a set of pattern, induce the trend etc. While, classical AI, on the other hand, is more concerned with “deductive” thought given as a set of constraints, deduce a conclusion etc.
Ans: A* algorithm is based on best first search method, as it gives an idea of optimization and quick choose of path, and all characteristics lie in A* algorithm.
Ans: A hybrid Bayesian network contains both a discrete and continuous variables.
Ans: Anything perceives its environment by sensors and acts upon an environment by effectors are known as Agent. Agent includes Robots, Programs, and Humans etc.
Ans: In AI, Prolog is a programming language based on logic.
Ans: There are many, some are 'problems' and some are 'techniques'.
Automatic Programming - The task of describing what a program should do and having the AI system 'write' the program.
Bayesian Networks - A technique of structuring and inference with probabilistic information. (Part of the "machine learning" problem).
Constraint Satisfaction - solving NP-complete problems, using a variety of techniques.
Knowledge Engineering/Representation - turning what we know about particular domain into a form in which a computer can understand it.
Machine Learning - Programs that learn from experience or data.
Natural Language Processing (NLP) - Processing and (perhaps) understanding human ("natural") language also known as computational linguistics.
Neural Networks (NN) - The study of programs that function in a manner similar to how animal brains do.
Planning - given a set of actions, a goal state, and a present state, decide which actions must be taken so that the present state is turned into the goal state
Robotics - The intersection of AI and robotics, this field tries to get (usually mobile) robots to act intelligently.
Speech Recognition - Conversion of speech into text.
Ans: Strong AI makes strong claims that computers can be made to think on a level equal to humans while weak AI simply predicts that some features that are resembling to human intelligence can be incorporated to computer to make it more useful tools.
Ans: The objective of an Inductive Logic Programming is to come up with a set of sentences for the hypothesis such that the entailment constraint is satisfied.
Ans: There are three literals available in top-down inductive learning methods they are
Ans: Hidden Markov Models are a ubiquitous tool for modeling time series data or to model sequence behavior. They are used in almost all current speech recognition systems.
Ans: The state of the process in HMM’s model is described by a ‘Single Discrete Random Variable’.
Ans: ‘Possible States of the World’ is the possible values of the variable in HMM’s.
Ans: While staying within the HMM network, the additional state variables can be added to a temporal model.
Ans: In Artificial Intelligence, to extract the meaning from the group of sentences semantic analysis is used.