lecture 1 introduction n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Lecture 1 – Introduction PowerPoint Presentation
Download Presentation
Lecture 1 – Introduction

Loading in 2 Seconds...

play fullscreen
1 / 14

Lecture 1 – Introduction - PowerPoint PPT Presentation


  • 87 Views
  • Uploaded on

Lecture 1 – Introduction. Shuaiqiang Wang ( 王帅强 ) School of Computer Science and Technology Shandong University of Finance and Economics http ://alpha.sdufe.edu.cn/swang/ shqiang.wang@gmail.com. About Me. Office: SDFIE center ( 舜耕校区 金融信息工程中心 ) Education:

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Lecture 1 – Introduction' - danica


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
lecture 1 introduction

Lecture 1 – Introduction

Shuaiqiang Wang (王帅强)

School of Computer Science and Technology

Shandong University of Finance and Economics

http://alpha.sdufe.edu.cn/swang/

shqiang.wang@gmail.com

about me
About Me
  • Office: SDFIE center (舜耕校区 金融信息工程中心)
  • Education:
    • 2000.09 – 2009.12, Shandong Univ. (B.Sc. & Ph.D.)
    • 2009.07 – 2009.09, Hong Kong Baptist Univ. (visit)
  • Work Experience:
    • 2010.01 – 2011.02, Texas State Univ. (Postdoc)
    • 2011.03 – Current, SDUFE (Associate Prof.)
  • Research Interests
    • Data mining; Machine learning; Information retrieval
about this course
About This Course
  • I prepared everything carefully from several relevant courses!
  • I removed those out-of-date contents while introduced some state-of-the-art, useful and interesting chapters!
  • So, enjoy it!
  • Part I: Optimization
  • Part II: Frequent Pattern Mining
  • Part III: Clustering
  • Part IV: Classification
  • Part V: Search Engine and Recommender Systems
acting humanly turing test
Acting Humanly: Turing Test
  • Turing (1950) "Computing machinery and intelligence":
  • "Can machines think?"  "Can machines behave intelligently?"
  • Operational test for intelligent behavior: the Imitation Game
  • Predicted that by 2000, a machine might have a 30% chance of fooling a lay person for 5 minutes
  • Suggested major components of AI: knowledge, reasoning, language understanding, learning
thinking humanly cognitive modeling
Thinking Humanly: Cognitive Modeling
  • 1960s "cognitive revolution": information-processing psychology
  • Requires scientific theories of internal activities of the brain
  • -- How to validate? Requires

1) Predicting and testing behavior of human subjects (top-down)

or 2) Direct identification from neurological data (bottom-up)

Both approaches (roughly, Cognitive Science and Cognitive Neuroscience) are now distinct from AI!

thinking rationally laws of thought
Thinking Rationally: “Laws of Thought"
  • Aristotle: what are correct arguments/thought processes?
  • Several Greek schools developed various forms of logic: notation and rules of derivation for thoughts; may or may not have proceeded to the idea of mechanization
  • Direct line through mathematics and philosophy to modern AI
  • Problems:
    • Not all intelligent behavior is mediated by logical deliberation
    • What is the purpose of thinking? What thoughts should I have?
acting rationally rational agent
Acting Rationally: Rational Agent
  • Rational behavior: doing the right thing
  • The right thing: that which is expected to maximize goal achievement, given the available information
  • Doesn't necessarily involve thinking – e.g., blinking reflex – but thinking should be in the service of rational action
history of ai 1
History of AI (1)
  • 1943 McCulloch & Pitts: Boolean circuit model of brain
  • 1950 Turing’s “Computing Machinery and Intelligence”
  • 1950s Early AI programs, including Samuel’s checkers program,
  • Newell & Simon’s Logic Theorist, Gelernter’s Geometry Engine
  • 1956 Dartmouth meeting: “Artificial Intelligence” adopted
history of ai 2
History of AI(2)
  • 1965 Robinson’s complete algorithm for logical reasoning
  • 1966–74 AI discovers computational complexity
  • Neural network research almost disappears
  • 1969–79 Early development of knowledge-based systems
  • 1980–88 Expert systems industry booms
history of ai 3
History of AI(3)
  • 1988–93 Expert systems industry busts: “AI Winter”
  • 1985–95 Neural networks return to popularity
  • 1988– Resurgence of probability; general increase in technical depth
  • “Nouvelle AI”: ALife, GAs, soft computing
  • 1995– Agents, agents, everywhere . . .
  • 2003– Human-level AI back on the agenda
state of the art
State-of-the-art
  • Decision Support
  • Data Mining
  • Machine Learning
  • Natural Language Processing
  • Web Intelligence
  • Information Retrieval
  • Pattern Recognition
  • Intelligent City
important issues
Important Issues
  • The ultimate goal of AI
    • E.g., machine translation can be done based on dictionaries, data and rules, without any understanding of languages
      • “How old are you?”
      • 怎么老是你?
  • Representation
    • Logic or Probability?