an introduction to artificial intelligence ce-40417 lecture 1b: history of a.i

An introduction to Artificial An introduction to Artificial IntelligenceIntelligence CE-40417 CE-40417

An introduction to Artificial An introduction to Artificial IntelligenceIntelligence CE-40417 CE-40417

Lecture 1b: History of A.I.Lecture 1b: History of A.I.

It started by science fiction…It started by science fiction…

• In 1921, the Czech author Karel Capek produced the play R.U.R. (Rossum's Universal Robots).

• In 1921, the Czech author Karel Capek produced the play R.U.R. (Rossum's Universal Robots).

"CHEAP LABOR. ROSSUM'S ROBOTS." "ROBOTS FOR THE TROPICS. 150 DOLLARS EACH.""EVERYONE SHOULD BUY HIS OWN ROBOT." "DO YOU WANT TO CHEAPEN YOUR OUTPUT? ORDER ROSSUM'S ROBOTS"

The Gestation of A.I.1943-1956


• Modeling of Neurons– Warren Mc Culloch & Walter Pitts, 1943

• Learning by Neurons– Donald Hebb, 1949

• Implementation of Neurons– Marvin Minsky & Dean Edmonds, 1951

• Modeling of Neurons– Warren Mc Culloch & Walter Pitts, 1943

• Learning by Neurons– Donald Hebb, 1949

• Implementation of Neurons– Marvin Minsky & Dean Edmonds, 1951



• First Chess Player Program– Claude Shannon & Alan Turing, 1950s

• Logic Theorist– Newell & Simon from CMU.

• First Chess Player Program– Claude Shannon & Alan Turing, 1950s

• Logic Theorist– Newell & Simon from CMU.



• Dartmouth Conf.: Birth place of AI, 1956• Dartmouth Conf.: Birth place of AI, 1956

John McCarthy

Marvin Minsky

Cloud E. Shannon

Nathaniel Rochester

Early Enthusiasm,Great Expectations

1952-1969


1952-1969

• Successful Years, with limited resources.

• General Problem Solver – CMU– The first program, emulating human thinking.

• Geometry Theorem Prover – IBM– Gelenter, 1959

• Successful Years, with limited resources.

• General Problem Solver – CMU– The first program, emulating human thinking.

• Geometry Theorem Prover – IBM– Gelenter, 1959


1952-1969


1952-1969

• Checkers Player Machines– Arthur Samuel, 1952-– Presenting Learning…– A TV Show!

• Invention(!) of LISP and Time Sharing– McCarthy, MIT, 1958

• Checkers Player Machines– Arthur Samuel, 1952-– Presenting Learning…– A TV Show!

• Invention(!) of LISP and Time Sharing– McCarthy, MIT, 1958


1952-1969


1952-1969

• Advice Taker– McCarthy, MIT, 1958– General Knowledge, Not Implemented

• Resolution Algorithm– Robinson, ~1963

• Planning Systems– Green, 1969, Stanford

• Advice Taker– McCarthy, MIT, 1958– General Knowledge, Not Implemented

• Resolution Algorithm– Robinson, ~1963

• Planning Systems– Green, 1969, Stanford


1952-1969


1952-1969

• Micro Worlds– Minskey, MIT, 1963

• Blocks World

• ANALOGY– Tom Evans, 1968, MIT

• Semantic Information Retrieval (SIR)– Bertram Raphael, 1968– Inputs in English

• Micro Worlds– Minskey, MIT, 1963

• Blocks World

• ANALOGY– Tom Evans, 1968, MIT

• Semantic Information Retrieval (SIR)– Bertram Raphael, 1968– Inputs in English


1952-1969


1952-1969

• STUDENT– Daniel Bobrow, 1967

• If the number of customers Tom gets are twice the square of 20 percent of the number of advertisements he runs and the number of advertisements he runs are 45, what is the number of customers Tom gets.

• STUDENT– Daniel Bobrow, 1967

• If the number of customers Tom gets are twice the square of 20 percent of the number of advertisements he runs and the number of advertisements he runs are 45, what is the number of customers Tom gets.


1952-1969


1952-1969

• Shakey , Stanford, 1966-1972

Shakey had a TV camera, a triangulating range finder, and bump sensors, and was connected to DEC PDP-10 and PDP-15 computers via radio and video links. Shakey used programs for perception, world-modeling, and acting. Low-level action routines took care of simple moving, turning, and route planning. Intermediate level actions strung the low level ones together in ways that robustly accomplished more complex tasks. The highest level programs could make and execute plans to achieve goals given it by a user. The system also generalized and saved these plans for possible future use.

• Shakey , Stanford, 1966-1972

Shakey had a TV camera, a triangulating range finder, and bump sensors, and was connected to DEC PDP-10 and PDP-15 computers via radio and video links. Shakey used programs for perception, world-modeling, and acting. Low-level action routines took care of simple moving, turning, and route planning. Intermediate level actions strung the low level ones together in ways that robustly accomplished more complex tasks. The highest level programs could make and execute plans to achieve goals given it by a user. The system also generalized and saved these plans for possible future use.


1952-1969


1952-1969

• Flourishing of Neural Networks– Learning Large Amounts of Data

• Adalines, 1962, Widrow• Perceptrons, 1962

• Flourishing of Neural Networks– Learning Large Amounts of Data

• Adalines, 1962, Widrow• Perceptrons, 1962

Science Fiction…Science Fiction…

• Isaac Asimov– 1950- – 43 Novels & 250 Short Stories

• The three laws of robotics• A robot may not injure a human being, or, through inaction,

allow a human being to come to harm. • A robot must obey the orders given it by human beings

except where such orders would conflict with the First Law. • A robot must protect its own existence as long as such

protection does not conflict with the First or Second Law.

• Isaac Asimov– 1950- – 43 Novels & 250 Short Stories

• The three laws of robotics• A robot may not injure a human being, or, through inaction,

allow a human being to come to harm. • A robot must obey the orders given it by human beings

except where such orders would conflict with the First Law. • A robot must protect its own existence as long as such

protection does not conflict with the First or Second Law.


• Sir Arthur C. Clark– 2001, A Space Odyssey, 1968

• Sir Arthur C. Clark– 2001, A Space Odyssey, 1968


• Star Trek– 726 episodes from 1966-2005.– 10 Movies

• Star Trek– 726 episodes from 1966-2005.– 10 Movies

Data: "And for a time, I was tempted by her offer."Picard: "How long a time?"Data: "0.68 seconds, sir. For an android, that is nearly an eternity."

– While lamenting the Borg Queen and her destruction in First Contact.

http://upload.wikimedia.org/wikipedia/en/7/75/NCC-1701-E.jpg

A dose of reality1966-1974


• Herbert Simon, 1957

– The power of A.I. will increase so rapidly that in a visible future, the range of problems they can handle will be coextensive to that of human.

– With in 10 years, the computer will be chess champions and mathematic theorem provers.

• Herbert Simon, 1957

– The power of A.I. will increase so rapidly that in a visible future, the range of problems they can handle will be coextensive to that of human.

– With in 10 years, the computer will be chess champions and mathematic theorem provers.



• Automatic Translation after Sputnik lunch, 1957.– Famous Failures:

• The spirit is willing, but the flesh is weak the vodka is good but the meat is rotten.

• Out of mind, out of sight Invisible idiot!

– 1966, “there is no M.T. for general scientific text and there would be no in immediate prospect.” All canceled.

• Automatic Translation after Sputnik lunch, 1957.– Famous Failures:

• The spirit is willing, but the flesh is weak the vodka is good but the meat is rotten.

• Out of mind, out of sight Invisible idiot!

– 1966, “there is no M.T. for general scientific text and there would be no in immediate prospect.” All canceled.



• AI based on simple facts and informed search. (Micro Words)

– Fine for a few objects and facts.– Combinatorial Explosion

– Logical feasibility will not necessarily result in practical possibility.

• AI based on simple facts and informed search. (Micro Words)

– Fine for a few objects and facts.– Combinatorial Explosion

– Logical feasibility will not necessarily result in practical possibility.



• Lighthill report to British Government, 1973

– Cancellation of all AI research in G.B. except to universities. – Combinatorial Explosion

• Minskey and Papert, 1969:– Neural Networks can’t learn but trivials.

• Lighthill report to British Government, 1973

– Cancellation of all AI research in G.B. except to universities. – Combinatorial Explosion

• Minskey and Papert, 1969:– Neural Networks can’t learn but trivials.

Knowledge Based Systems1969-1979


• DENDRAL– Buchanan et al, 1969, Stanford

• To have general knowledge about a field and required inference rules.

– Extracting Analytic Chemists’ Expertise– Inference based on given facts.

• DENDRAL– Buchanan et al, 1969, Stanford

• To have general knowledge about a field and required inference rules.

– Extracting Analytic Chemists’ Expertise– Inference based on given facts.



• MYCIN– Feigenbaum, et al, 1971– Diagnosis of blood infections with 450 rules.– Better than junior doctor and comparable with

experts.

• PROSPECTOR– Duda et al, 1979

• Recommendation of exploratory drilling positions at a geological site.

• MYCIN– Feigenbaum, et al, 1971– Diagnosis of blood infections with 450 rules.– Better than junior doctor and comparable with

experts.

• PROSPECTOR– Duda et al, 1979

• Recommendation of exploratory drilling positions at a geological site.



• Schank, Yale:– There is no such thing as language syntax.– Its meaning that matters

• LUNAR, Williams & Woods, 1973– A natural language interface to Apollo moon

mission database.

• Schank, Yale:– There is no such thing as language syntax.– Its meaning that matters

• LUNAR, Williams & Woods, 1973– A natural language interface to Apollo moon

mission database.

AI Becomes industry1980-1988

AI Becomes industry1980-1988

• R1 Expert System at DEC, 1982– Configuration of computer systems.– Saving $40 million per year.

• The Fifth Generation Project– 10 year to build a Prolog processing machine by

Japanese.– Counter attacks in U.S. and G.B.

• From a few million in 1980 to $2 billion in 1988.

• R1 Expert System at DEC, 1982– Configuration of computer systems.– Saving $40 million per year.

• The Fifth Generation Project– 10 year to build a Prolog processing machine by

Japanese.– Counter attacks in U.S. and G.B.

• From a few million in 1980 to $2 billion in 1988.

The return of neural networks1986-

The return of neural networks1986-

• Analysis of storage capacity– Hopfield, 1982

• Neural Models of Memory– Different psychologists, 1980s

• Reinvention of BACK-PROPAGATION– First in 1969, then in 1986.

• Connectionism School

• Analysis of storage capacity– Hopfield, 1982

• Neural Models of Memory– Different psychologists, 1980s

• Reinvention of BACK-PROPAGATION– First in 1969, then in 1986.

• Connectionism School

Recent Events1987-

Recent Events1987-

• Neats defeated Scruffies

– Continual of previous theories vs. proposing brand new ones.

– Working on real domains vs. toy problems.

• Neats defeated Scruffies

– Continual of previous theories vs. proposing brand new ones.

– Working on real domains vs. toy problems.

Recent Events1987-

Recent Events1987-

• Speech Recognition– Several ad hoc methods in 1970s.– Hidden Markov Models

• Based on Years of Mathematics• Training with real data

– SR and OCR at industry.

• Speech Recognition– Several ad hoc methods in 1970s.– Hidden Markov Models

• Based on Years of Mathematics• Training with real data

– SR and OCR at industry.

Recent Events1987-

Recent Events1987-

• Planning– Extending previous attempts

• From early laying with Micorwords

– To• Factory workspace planning• Space Mission Planning• Scheduling• …

• Planning– Extending previous attempts

• From early laying with Micorwords

– To• Factory workspace planning• Space Mission Planning• Scheduling• …

Recent Events1987-

Recent Events1987-

• Belief Networks,1985– Dealing with uncertainties in reasoning

• Similar Advances in– Robotics, Vision, Learning, Knowledge

Representation, Distributed Intelligence

• Belief Networks,1985– Dealing with uncertainties in reasoning

• Similar Advances in– Robotics, Vision, Learning, Knowledge

Representation, Distributed Intelligence

State of the ArtState of the Art

• Chess Grand Masters

• Speech Understanding Interfaces

• Mission Analyzers

• Auto-Drivers

• Expert Systems

• Traffic Control

• …

• Chess Grand Masters

• Speech Understanding Interfaces

• Mission Analyzers

• Auto-Drivers

• Expert Systems

• Traffic Control

• …

an introduction to artificial intelligence ce-40417 lecture 1b: history of a.i

Documents

stanford slide

english slide

great expectations

early enthusiasm

number of customers

number of advertisements

neurons donald hebb

stanford advice taker