Introduction to AI

Introduction to AI

1. Sensor Simulation

   • Sensor simulation is the imitation of human sensory abilities or skills.

2. Bayesian Networks

   • Is a probabilistic graphical model that represents a set of random variables and their conditional dependencies.

3. Automatic Programming

   • It’s when a computer program’s code is written by a machine.

4. Laws of Robotic

   • Law number 1: A robot may not injure a human being or, through inaction, allow a human being to come to harm Law number 2: A robot must obey the orders given it by human beings, except where such orders would conflict with the First Law Law number 3: A robot must protect its own existence as long as such protection does not conflict with the First or Second Laws

5. Natural Language

   • Natural language is primarily focused in the design of software that’s able to accept and interpret and execute instructions that users give.

6. Robotics

   • Is the science and technique to create machines that manipulate the environment, its origins come from science fiction.

7. Fuzzy Logic

   • It’s a mathematical technique for the treatment of inaccurate data or problems with many solutions. It uses values from 0 to 1 and is similar to human logic.

8. Artificial Neutrat Networks

   • An artificial neural network (ANN) is a software designed to mimic the thought processes of humans. ANN’s learn by the trial and error method.

9. Expert System

   • Expert Systems is the area of AI that is more related to supporting the decision-making process in organizations. Knowledge bases are composed of a set of common sense rules called “Heuristic knowledge”. This knowledge is gained through experience.

10. Intelligent Agents

    • An intelligent agents Is a program that is designed to perform at certain specific knowledge and is usually used in repetitive tasks. They are often programmed for the preferences of a person.