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Artificial Intelligence Introduction

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Artificial Intelligence Introduction

  1. 1. By Kaushalendra Artificial Intelligence
  2. 2. Agenda • What is intelligence? • What is artificial intelligence? • History of A.I. • Type of A.I. • Turing test & Chinese room test • Intelligent agents • Agents & Environment • Human intelligence Vs A.I. • A.I. Vs Conventional computing • A.I and our society • Our personal opinion • Conclusion
  3. 3. • Intelligence is the ability to learn about, learn from, understand, and interact with one’s environment. • This general ability consists of a number of specific abilities, which include these specific abilities: – Adaptability to a new environment or to changes in the current environment – Capacity for knowledge and the ability to acquire it – Capacity for reason and abstract thought – Ability to comprehend relationships – Ability to evaluate and judge – Capacity for original and productive thought
  4. 4. What Is Artificial Intelligence???  Artificial Intelligence (AI) is usually defined as the science of making computers do things that require intelligence when done by humans.  Basically,AI is the study of how to make computers do things which, at the moment, people do better
  5. 5. A Brief History of AI 1956: John McCarthy coins phrase “artificial intelligence” 1952-62: Arthur Samuel writes the first AI game program to challenge a world champion, in part due to learning. 1950’s-60’s: Masterman et. al at Cambridge create semantic nets that do machine translation. 1965: Joseph Weizenbaum creates ELIZA, one of the earliest “chatterbots”
  6. 6. 1967: Feigenbaum et. al create Dendral, the first useful knowledge-based agent that interpreted mass spectrographs. 1969: Shakey the robot combines movement, perception and problem solving. 1985: ALVINN, “an autonomous land vehicle in a neural network” navigates across the country (2800 miles). Early 1990’s: Gerry Tesauro creates TD-Gammon, a learning backgammon agent that vies with championship players
  7. 7. How Does AI Works?? Artificial intelligence works with the help of • Artificial Neurons (Artificial Neural Network) And • Scientific theorems(If-Then Statements, Logics)
  8. 8. What is Neural Networking??  Artificial neural networks are composed of interconnecting artificial neurons (programming constructs that mimic the properties of biological neurons).
  9. 9. Turing Test The Turing test is a test of a machine’s  ability to exhibit intelligent behavior  equivalent to, or indistinguishable from  human. In this test a human judge engages in natural  language conversations with a human and a machine  designed to generate performance indistinguishable  from that of a human being. All participants are  separated from one another. If the judge cannot  reliably tell the machine from the human, the  machine is said to have passed the test. Imitation Game Test!!!!
  10. 10. Intelligent agents 04/18/14 10 Actions Agent Sensors Actuator s ? Environment Percep ts • An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators • Percept refers to agents perceptual inputs • Percept sequence: Complete history of everything the agent has perceived. • Performance Measure: Criterion for success for agent
  11. 11. • The agent function maps from percept histories to actions: [f: P*  A] Agents and environments
  12. 12. • Four basic types in order of increasing generality: • Simple reflex agents • Model-based reflex agents / Agent that keep track of the world. • Goal-based agents • Utility-based agents Agent types
  13. 13. Simple reflex agents
  14. 14. Model-based reflex agents
  15. 15. Goal-based agents
  16. 16. Utility-based agents
  17. 17. • Fully observable (vs. partially observable): An agent's sensors give it access to the complete state of the environment at each point in time. • Deterministic (vs. stochastic): The next state of the environment is completely determined by the current state and the action executed by the agent. • Episodic (vs. sequential): The agent's experience is divided into atomic "episodes" (each episode consists of the agent perceiving and then performing a single action), and the choice of action in each episode depends only on the episode itself. Environment types
  18. 18. *PEAS • PEAS: Performance measure, Environment, Actuators, Sensors • Consider, e.g., the task of designing an automated taxi driver: o Performance measure o Environment o Actuators o Sensors
  19. 19. *PEAS • Example of an automated taxi driver o Performance measure: Safe, fast, legal, comfortable trip, maximize profits o Environment: Roads, other traffic, pedestrians, customers o Actuators: Steering wheel, accelerator, brake, signal, horn o Sensors: Cameras, sonar, speedometer, GPS, odometer, engine sensors, keyboard
  20. 20. Applications of Expert Systems LITHIAN: Gives advice to archaeologists examining stone tools DENDRAL: Used to identify the structure of chemical compounds by analyzing mass spectra. First used in 1965 at stanford univesity.
  21. 21. There are Three ways that A.I learns Failure Driven Learning Learning by being Told Learning by Exploration
  22. 22. Resemblance To Human Mind.... The special ability of artificial intelligence is to reach a solution based on facts rather than on a preset series of steps —is what most closely resembles the thinking function of the human brain
  23. 23. Human Intelligence VS Artificial Intelligence Human Intelligence • Intuition, Common sense, Judgement, Creativity, Beliefs etc • The ability to demonstrate their intelligence by communicating effectively • Plausible Reasoning and Critical thinking Artificial Intelligence • Ability to simulate human behavior and cognitive processes • Capture and preserve human expertise • Fast Response. The ability to comprehend large amounts of data quickly. Pros
  24. 24. Human Intelligence VS Artificial Intelligence Human Intelligence • Humans are fallible • They have limited knowledge bases • Information processing of serial nature proceed very slowly in the brain as compared to computers • Humans are unable to retain large amounts of data in memory. Artificial Intelligence • No “common sense” • Cannot readily deal with “mixed” knowledge • May have high development costs • Raise legal and ethical concerns Cons
  25. 25. Artificial Intelligence VS Conventional Computing Artificial Intelligence • AI software uses the techniques of search and pattern matching • Programmers design AI software to give the computer only the problem, not the steps necessary to solve it Conventional Computing • Conventional computer software follow a logical series of steps to reach a conclusion • Computer programmers originally designed software that accomplished tasks by completing algorithms
  26. 26. • Our Perspective For Humans, Intelligence is no more than TAKING a right decision at right time And For Machines ,Artificial Intelligence is no more than CHOOSING a right decision at right time We think Artificial intelligence is the Second intelligence ever to exist
  27. 27. Conclusion • AI is at the centre of a new enterprise to build computational models of intelligence. • The main assumption is that intelligence (human or otherwise) can be represented in terms of symbol structures and symbolic operations which can be programmed in a digital computer.
  28. 28. Thank You Artificial Intelligence Our Attempt To Build Models Of Ourselves Submitted by - Kaushalendra Singh Rajput (2k12/EC/89)

Notes de l'éditeur

  • The important aspects of human intelligence seem to following the use of intuition, common sense, judgment, creativity, goal directedness, plausible reasoning, knowledge and beliefs.
    Meaning of intelligence is not human brain’s information processing ability but the ability of humans to demonstrate their intelligence by communicating effectively.

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