What is AI?

it is not easy to define AI

What is intelligence?

Learning (-> Skill, Knowledge)

Knowledge (-> infomation / fact, reasoning-thinking process)

Improvement over time = adaptability

Scalability

Generalization

What is effect of learning or generalization?

Problem Solving (“Capability of doing something”)

What are input and output of reasoning?

Human is most intelligent being.

Retrospect yourself open new area of intelligence.

not just fact

drive knowledge from given fact

Assessment

• 10 assignment
• 40 midterm
• 40 final
• 10 attendance

1. What is AI

Acting humanly: The Turing test approach

The Turing test, proposed by Alan Turing (1950), was designed as a thought experiment that would sidestep the philosophical vaueness of the question “Can a machine think?”. The computer would need the following capacilities:

• natural language processing to communicate successfully in a human language;
• knowledge representation to store what it knows or hears;
• automated reasoning to answer questions and to draw new conclusions;
• machine learning to adapt to new circumstances and to detect and extrapolate patterns

Other researchers have proposed a total Turing test, which requires interaction with objects and people in the real world. To pass the total Turing test, a robot will need

• computer vision and speech recognition to perceive the world;
• robotics to manipulate objects and move about.

4가지 접근

• Thinking humanly: The cognitive modeling approach
• Thinking rationally: The “laws of thought: approach
• Acting rationally: The rational agent approach
• Beneficial machines

2. The Foundations of Artificial Intellgience

We provide a bried history of the disciplines that contributed ideas, viewpoints and techniques

• Philosophy
• Mathematics
• Economics
• Neuroscience
• Psycholoy
• Computer Engineering

Control theory and cybernetics

Modern control theory, especially the branch known as stochastic optimal control, has as its goal the design of systems that maximize a cost function over time. This roughly matches the standard model of AI: designing systems that behave optimally. Why, then, are AI and control theory two different fields, despite the close connections among their founders? The answer lies in the close coupling between the mathematical techniques that were familiar to the participants and the corresponding sets of problems that were encompassed in each world view. Calculus and matrix algebra, the tools of control theory, lend themselves to systems that are describable by fixed sets of continuous variables, whereas AI was founded in part as a way to escape from these perceived limitations. The tools of logical inference and computation allowed AI researchers to consider problems such as language, vision, and symbolic planning that fell completely outside the control theorist’s purview.

• Linguistics