人工智能原理复习1

What is artificial intelligence?

A (Short) History of AI

1940-1950: Early days 1943: McCulloch & Pitts: Boolean circuit model of brain 1950: Turing's “Computing Machinery and Intelligence”

1950—70: The golden years! 1950s: Early AI programs, including Samuel's checkers program, Newell & Simon's Logic Theorist, Gelernter's Geometry Engine 1956: Dartmouth meeting: “Artificial Intelligence” adopted 1965: Robinson's complete algorithm for logical reasoning

1970—90: Knowledge-based approaches 1969—79: Early development of knowledge-based systems 1980—88: Expert systems industry booms 1988—93: Expert systems industry busts: “AI Winter”

1990—: Statistical approaches Resurgence of probability, focus on uncertainty General increase in technical depth Agents and learning systems… “AI Spring”?

2000—: Where are we now?

上面需要注意的点是：

1950: Turing's “Computing Machinery and Intelligence”

1956: Dartmouth meeting: “Artificial Intelligence” adopted

Game Agents（一个智能体是一个具有感知及行动的实体）

Classic Moment: May, '97: Deep Blue vs. Kasparov First match won against world champion “Intelligent creative” play 200 million board positions per second Humans understood 99.9 of Deep Blue's moves Can do about the same now with a PC cluster

1996: Kasparov Beats Deep Blue “I could feel --- I could smell --- a new kind of intelligence across the table.”

1997: Deep Blue Beats Kasparov “Deep Blue hasn't proven anything.”

Reinforcement learning

注：DeepMind 是一个专注于人工智能研究的公司，而 OpenSpiel 是 DeepMind 开发的一个开源库，用于研究和实现各种游戏和强化学习算法。

What is Artifical Intelligence?---Definition of textbook

Think like people

Act like people

Think rationally

Act rationally

Human Intelligence

Brains (human minds) are very good at making rational decisions, but not perfect

Language -> Concept -> Rule

Stopped making wings that flap (蝴蝶效应嘛这句话啥意思哈哈哈哈哈看不懂)

人类大约20万年前就形成了现在的解刨结构；
在接下来的15万年中，人类并没有发生较大的变化；
在大约5万年前，一小撮人类发明出人类区别于其他物种的能力，（虽然只有极少数的个体，就像是跑程序，只有极少数个体能够寻找到更优的位置，他们就能带领整个群体走向更好的区域），也就是使用语言（举例，袋鼠摇，管晨辰）（语言->概念->规则）

思考，感知，行动

智能是关于什么的智能？thinking , perception, action （什么是thinking，伽利略比萨斜塔，大球、小球、大球+小球，得到矛盾）

The model of that （1000瓶水，10只小白鼠，一次实验）（概率论模型，均匀分布，星座，1/12）

The representation 表示

The constraints 约束

The algorithm 算法

Desiging a rational agent that selects actions that maximize its (expected) utility.

This course is about:

Learning to recognize when and how a new problem can be solved with an existing technique

Learning the mechanism of numerious algorithms

Rational Decisions

We’ll use the term rational in a very specific, technical way:

Rational: maximally achieving pre-defined goals Rationality only concerns what decisions are made (not the thought process behind them) Goals are expressed in terms of the utility of outcomes Being rational means maximizing your expected utility