Artificial Intelligence

Artificial Intelligence

AI is the science of making machines do things that would require intelligence if done by men. It includes reasoning, learning, planning, speech recognition, vision, and language understanding. These machines are being used today in a wide variety of applications, such as monitoring credit card fraud, making autonomous decisions on space missions, watching for attacks from computer network hackers, diagnosing faults in aircraft, enabling human–machine speech interfaces, and making the characters in a video game behave in a more human-like way.

The main unifying theme is the idea of an intelligent agent. We define the AI as the study of agents that receive percepts from the environment and perform actions. Each such agent implements a function that maps percepts sequences to actions, and we cover different ways to represent these functions, such as real-time conditional planners, neural networks, and decision theoretic systems. We treat robotics and vision as occurring in the service of achieving goals.

Eliza, the program was able to converse about any subject, because it stored subject information in data banks.

Keywords: Turing test – Intelligent agents – Neural Networks – Genetic Programming – Planning – Fuzzy Logic – Robotics – Pattern recognition – Natural language processing – Deep blue – Eliza – video clip.

Index:

Introduction

Turing test

Classification

Intelligent agents

What belongs to AI?

Applications

Chess and AI

Computer Vs. Human Brain

Fuzzy-Logic and AI

Eliza

Conclusion (AI present & future)

References

1. Introduction

After WWII, a number of people independently started to work on intelligent machines. The English mathematician Alan Turing gave a lecture on it in 1947. I would compare attempts to create AI with man’s historical attempts at flight.

2. Turing test (Article of Computational Intelligence: 1950)

He argued that if the machine could successfully pretend to be human to a knowledgeable observer then you certainly should consider it intelligent. The observer could interact with the machine and a human by teletype (to avoid requiring that the machine imitate the appearance or voice of the person), and the human would try to persuade the observer that it was human and the machine would try to fool the observer.

3. Classification

This is a discipline with two strands: science and engineering. The scientific strand attempts to understand the requirements for, and mechanisms enabling, intelligence of various kinds in humans, other animals and information processing machines and robots. The engineering strand attempts to apply such knowledge in designing useful new kinds of machines and helping us to deal more effectively with natural intelligence, e.g. in education and therapy.

Bottom-up theorists believe the best way to achieve artificial intelligence is to build electronic replicas of the human brain’s complex network of neurons, while the top-down approach attempts to mimic the brain’s behavior with computer programs. Moreover there is a lot of difference between the AI simulated system and a program with the large database. This is discussed later on under the topic of chess-AI.

4. Intelligent Agents

An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators. An agent’s percept sequence is the complete history of everything the agent has ever perceived.

A rational agent is one that does the right thing. A Performance