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Artificial intelligence

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Artificial intelligence

  1. 1. BY, MIHIR SHAH
  2. 2. INTRODUCTION Alan Turning is considered as the father of Artificial Intelligence. The other pioneers in the field of AI are John McCarthy, D.Lenat, Alan Maurveraur and others.Artificial intelligence is the part of computer science concerned with designing intelligent computer system that is systems which exhibit the characteristics we associate with intelligence in humans. It deals with symbolic ,non-algorithmic methods of problem solving
  3. 3. Neural Network and Artificial Intelligence Neural networks, as used in artificial intelligence, have traditionally been viewed as simplified models of neural processing in the brain.  A subject of current research in theoretical neuroscience is the question surrounding the degree of complexity and the properties that individual neural elements should have to reproduce something resembling animal intelligence.
  4. 4. Fuzzy Logic Fuzzy logic is a form of multi-valued logic derived from fuzzy set theory to deal with reasoning that is approximate rather than precise. Just as in fuzzy set theory the set membership value is in range of 0 to 1, in fuzzy logic the degree of truth of a statement can range between 0 and 1 and is not constrained as in classic predicate logic. When linguistic variables are used, these degrees may be managed by some specific functions.
  5. 5. Characteristics of AI Deduction, reasoning, problem solving Early AI researchers developed algorithms that imitated the process of conscious, step-by-step reasoning that human beings use when they solve puzzles, play board games, or make logical deductions. By the late 80s and 90s, AI research had also developed highly successful methods for dealing with uncertain or incomplete information, employing concepts from probability and Economics
  6. 6.  Knowledge representation Knowledge representation and knowledge engineering are central to AI research. Many of the problems machines are expected to solve will require extensive knowledge about the world.  Among the things that AI needs to represent are: objects, properties, categories and relations between objects; situations, events, states and time; causes and effects; and many other, less well researched domains.
  7. 7. Planning Intelligent agents must be able to set goals and achieve them. They need a way to visualize the future and be able to make choices that maximize the utility of the available choices. Learning The idea behind machine learning is primarily concerned with the study and development of programs which learn from their experience
  8. 8. Natural language processing Natural language processing gives machines the ability to read and understand the languages human beings speak. Many researchers hope that such system would be able to acquire knowledge on its own, by reading the existing text available over the internet. Some straight-forward applications include information retrieval and
  9. 9. Perception  Perception is the ability to use input from sensors to deduce aspects of the world. Computer vision is the ability to analyze visual input. A few selected subproblems are speech recognition, facial recognition and object recognition Motion and Manipulation The field of robotics is closely related to AI. Intelligence is required for robots to be able to handle such tasks as object manipulation and navigation.
  10. 10. Genetic Algorithm (GA) A genetic algorithm (GA) is a search technique used in computing to find exact or approximate solutions to optimization and search problems. Genetic algorithms are categorized as global search heuristics.  Genetic algorithms are a particular class of evolutionary algorithms that use techniques inspired by evolution -ary biology such as inheritance, mutation, selection, and crossover .
  11. 11. APPLICATIONS OF AI Finance Financial institutions have long used artificial neural network systems to detect charges or claims outside of the norm, flagging these for human investigation. Heavy Industries Robots have proven effective in jobs that are very repetitive which may lead to mistakes or accidents due to a lapse in concentration and other jobs which humans may find degrading
  12. 12. Expert Systems Of all the application of artificial intelligence , expert systems are perhaps the most familiar and are certainly the most commercially successful. An expert system is basically an AI program which uses knowledge to solve the problems which would normally required a human expert. The system includes a reasoning mechanism for making choices and navigating around the search space for possible solution
  13. 13. Medicine A medical clinic can use artificial intelligence systems to organize bed schedules, make a staff rotation, and provide medical information. Artificial neural networks are used for medical diagnosis (such as in Concept Processing technology in EMR software), functioning as machine differential diagnosis. Aviation The Air Operations Division , AOD, uses for the rule based expert systems
  14. 14. Transportation Fuzzy logic controllers have been developed for automatic gearboxes in automobiles (the Audi TT, which utilizes Fuzzy logic, a number of Skoda variants also currently include a Fuzzy Logic based controller). Telecommunications Many telecommunications companies make use of heuristic search in the management of their workforces, for example BT Group has deployed heuristic search in a scheduling
  15. 15. Toys and games Artificial Intelligence for education, or leisure. This prospered greatly with the Digital Revolution, and helped introduce people, especially children, to a life of dealing with various types of AI, specifically in the form of Giga Pets, the Internet , and the first widely released robot, Furby. A mere year later an improved type of domestic robot was released in the form of Aibo, a robotic dog with intelligent features and autonomy.
  16. 16. The Main AI Languages The main programming languages used in AI are Lisp and Prolog. Both have features which make them suitable for AI programming, such as support for list processing, pattern matching and exploratory programming  LISP uses the list as its fundamental representation for data structures and programs (function definitions), and provides a wide range of built in functions for manipulating lists PROLOG is a language based on logic. In particular, it is based on first order predicate calculus
  17. 17. CONCLUSION It can be concluded that in spite of impressive achievements , on the hardware and software fronts it has not been possible to produce coordinated autonomous system which possess some of the basic abilities of a three year old child.  Information creation, Autonomy, Situated ness can be regarded as focuses for the AI research and development in future. In order to come up to these challenges, a lot of single methods have to be integrated into greater systems.

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