What is Artificial Intelligence? (Part 2)

What would a computer need to pass the Turing test?

• Natural language processing: to communicate with examiner.
• Knowledge representation: to store and retrieve information provided before or during interrogation.
• Automated reasoning: to use the stored information to answer questions and to draw new conclusions.
• Machine learning: to adapt to new circumstances and to detect and extrapolate patterns.
• Vision (for Total Turing test): to recognize the actions and various objects presented by the examiner.
• Motor control (total test): to act upon objects as requested.
• Other senses (total test): such as audition, smell, touch, etc.

How to achieve AI?

How is AI research done?

AI research has both theoretical and experimental sides. The experimental side has both basic and applied aspects.

There are two main lines of research:

• One is biological, based on the idea that since humans are intelligent, AI should study humans and imitate their psychology or physiology.
• The other is phenomenal, based on studying and formalizing common sense facts about the world and the problems that the world presents to the achievement of goals.

Branches of AI

• Logical AI
• Search
• Natural language processing
• pattern recognition
• Knowledge representation
• Inference From some facts, others can be inferred.
• Automated reasoning
• Learning from experience
• Planning To generate a strategy for achieving some goal
• Genetic programming
• Emotions???

AI State of the art

Have the following been achieved by AI?

• World-class chess playing
• Playing table tennis
• Cross-country driving
• Solving mathematical problems
• Discover and prove mathematical theories
• Engage in a meaningful conversation
• Understand spoken language
• Observe and understand human emotions
• Express emotions

Applications of AI

• Robotics
• Computer Vision
• Voice Recognition
• Natural Language Processing
• Expert Systems

Core AI Technologies

• Knowledge Representation
• Search Algorithms
• Inference
• Heuristics
• Learning
• Neural Networks
• Biomechanics

AI Programming Languages

PROLOG

PROgramming in LOGic

C++

XML

Extensible Markup Language

LISP

List Processing