History of AI. History of AI. History of AI. History of AI History of AI

Size: px

Start display at page:

Download "History of AI. History of AI. History of AI. History of AI History of AI"

Jerome Cross
5 years ago
Views:

1 Klassische Themen der Computerwissenschaften Artificial Intelligence History of AI Prof. Dr. Franz Wotawa The following slides are an excerpt from History of AI 5th century B.C. Aristotle introduced the syllogistic logic 16th century Famous story of the Golem who is said to be invented by Rabbi Loew of Prague (1580). 17th century Pascal created the first mechanical digital calculating machine (1642). Leibniz improved Pascal's machine (1673) 19th century Mary Shelley published the story Frankenstein (1818). George Boole developed a binary algebra Charles Babbage & Ada Byron (Lady Lovelace) worked on programmable mechanical calculating machines. History of AI 20th century - First Half Bertrand Russell and Alfred North Whitehead published Principia Mathematica, which revolutionaized formal logic. Warren McCulloch & Walter Pitts publish "A Logical Calculus of the Ideas Immanent in Nervous Activity" (1943), laying foundations for neural networks. Arturo Rosenblueth, Norbert Wiener & Julian Bigelow coin the term "cybernetics" in a 1943 paper. Wiener's popular book by that name published in A.M. Turing published "Computing Machinery and Intelligence" (1950). Claude Shannon published detailed analysis of chess playing as search (1950). History of AI John McCarthy coined the term "artificial intelligence" as the topic of the Dartmouth Conference, the first conference devoted to the subject. Demonstration of the first running AI program, the Logic Theorist (LT) written by Allan Newell, J.C. Shaw and Herbert Simon The General Problem Solver (GPS) demonstrated by Newell, Shaw & Simon John McCarthy (MIT) invented the Lisp language History of AI James Slagle (PhD dissertation, MIT) wrote (in Lisp) the first symbolic integration program, SAINT, which solved calculus problems at the college freshman level Thomas Evans' program, ANALOGY, written as part of his PhD work at MIT, demonstrated that computers can solve the same analogy problems as are given on IQ tests Edward A. Feigenbaum & Julian Feldman published Computers and Thought, the first collection of articles about artificial intelligence Danny Bobrow's dissertation at MIT (tech.report #1 from MIT's AI group, Project MAC), shows that computers can understand natural language well enough to solve algebra word problems correctly J. Alan Robinson invented a mechanical proof procedure, the Resolution Method, which allowed programs to work efficiently with formal logic as a representation language. Joseph Weizenbaum (MIT) built ELIZA, an interactive program that carries on a dialogue in English on any topic. It was a popular toy at AI centers on the ARPA-net when a version that "simulated" the dialogue of a psychotherapist was programmed Dendral program (Edward Feigenbaum, Joshua Lederberg, Bruce Buchanan, Georgia Sutherland at Stanford) demonstrated to interpret mass spectra on organic chemical compounds. First successful knowledge-based program for scientific reasoning Marvin Minsky & Seymour Papert publish Perceptrons, demonstrating limits of simple neural nets SRI robot, Shakey, demonstrated combining locomotion, perception and problem solving 1

History of AI 1970-79 History of AI 1980-89 Terry Winograd's PhD thesis (MIT) demonstrated the ability of computers to understand English sentences in a restricted world of children's blocks, in a

Prolog developed by Alain Colmerauer Ted Shortliffe's PhD dissertation on MYCIN (Stanford) demonstrated the power of rule-based systems for knowledge representation and inference in the domain of

Sometimes called the first expert system Marvin Minsky published his widely-read and influential article on Frames as a representation of knowledge, in which many ideas about schemas and semantic

2 History of AI History of AI Terry Winograd's PhD thesis (MIT) demonstrated the ability of computers to understand English sentences in a restricted world of children's blocks, in a coupling of his language understanding program, SHRDLU, with a robot arm that carried out instructions typed in English. Prolog developed by Alain Colmerauer Ted Shortliffe's PhD dissertation on MYCIN (Stanford) demonstrated the power of rule-based systems for knowledge representation and inference in the domain of medical diagnosis and therapy. Sometimes called the first expert system Marvin Minsky published his widely-read and influential article on Frames as a representation of knowledge, in which many ideas about schemas and semantic links are brought together The Meta-Dendral learning program produced new results in chemistry (some rules of mass spectrometry) the first scientific discoveries by a computer to be published in a refereed journal Randall Davis demonstrated the power of meta-level reasoning in his PhD dissertation at Stanford Drew McDermott & Jon Doyle at MIT, and John McCarthy at Stanford begin publishing work on non-monotonic logics and formal aspects of truth maintenance Lisp Machines developed and marketed First expert system shells and commercial applications James Allen invents the Interval Calculus, the first widely used formalization of temporal events Neural Networks become widely used with the Backpropagation algorithm (first described by Werbos in 1974) Marvin Minsky publishes The Society of Mind, a theoretical description of the mind as a collection of cooperating agents History of AI History of AI RoboCup 2006 Major advances in all areas of AI, with significant demonstrations in machine learning, intelligent tutoring, case -based reasoning, multi-agent planning, scheduling, uncertain reasoning, data mining, natural language understanding and translation, vision, virtual reality, games, and other topics Rod Brooks' COG Project at MIT, with numerous collaborators, makes significant progress in building a humanoid robot The Deep Blue chess program beats the current world chess champion, Garry Kasparov, in a widely followed match RoboCup series started 1997!! Web crawlers and other AI-based information extraction programs become essential in widespread use of the world -wide-web Interactive robot pets (a.k.a. "smart toys") become commercially available, realizing the vision of the 18th cen. novelty toy makers History of AI Robotic applications References & Links AAAI. AI Topics: History of AI at 50 Years - Artificial Intelligence Symposium ( at KI 2006 (17 June 2006, Bremen). "This year, the Artificial Intelligence community celebrates the golden anniversary of the 1956 Dartmouth Conference that marks the beginning of AI as a research field. This symposium will take stock of the promises and achievements of AI and looks ahead to the next 50 years. The meeting will be moderated by Wilfried Brauer (TU München / U Bremen)." Stuart Russel and Peter Norvig, Artificial Intelligence: A Modern Approach, 2nd Edition, Prentice Hall, 2003, ISBN-10: , ISBN-13: Aus Visa Magazin 4/2006 2

3 The Turing Test (TT) The Imitation Game (I)? The Imitation Game (II) The Turing Test (TT)??? The Turing Test - Summary Testing intelligence by answering the question Can machines communicate in natural language in a manner indistinguishable from that of a human being? Arguments against TT and some replies from Turing (see next slides) References: Ayse Pinar Saygin, Ilyas Cicekli, and Varol Akman, Turing Test: 50 Years later, Minds and Machines 10: , Kluwer, Arguments against TT (I) Heads in the sand objection: Thinking machines are not good because they would share human abilities (e.g. thinking). Mathematical objections: E.g. Gödel s Theorem (However, maybe intelligent machines can make mistakes) Arguments from consciousness: Machines should be aware about themselves. Extreme point of view Solipsism : The only way to really know whether a machine (or man) is thinking or not is to be that machine (or man). Also known as other minds problem. 3

4 Arguments against TT (II) Arguments from various disabilities: machines can never do X where X is something like have sense of humor. Lady Lovelace s objection: A machine cannot originate anything. Logic-based AI Logic-based AI Explicit vs. implicit knowledge Use logic for representing knowledge and for reasoning The representation of knowledge has an impact on the reasoning capabilities Explicit versus implicit knowledge Declarative versus procedural knowledge i 1.. i k 1 McCulloch-Pitts Neurons o Neural Networks The output is true if at least one of its inputs is true o = i 1 i k Knowledge can be distributed a b c a b c Procedural vs. declarative knowledge function prim (n:integer): boolean; var i: integer; begin if n <=1 then prim:=false. else begin i:=2; while (i<=trunc(sqrt(n))+1) and (n mod i <> 0) do i := i+1; prim := (n=2) or (n mod i <> 0) end end prim(n) ( n>1 m (teilt(m,n) (m=1 m=n) ) ) 4

5 Requirements for knowledge -based systems In Knowledge-based Systems (KBS, Expert Systems) knowledge has to be: explicit, and declarative Why logic? Somehow easy way for describing the world Close to natural language Almost problem independent Example: When it is raining the streets are wet and It is raining. Example Another example function wet (): boolean begin if raining then wet=true; else wet=false; end Formalising theory: 1. raining wet 2. raining Conlusion: wet Model: 1. birds can fly 2. penguins are birds 3. tweety is a bird 4. tweety is a penguin 5. penguins cannot fly But also dead birds cannot fly! Propositional Logic Syntax Set of basic propositions (atoms, atomic formulas): a,b,c,, p 1, Compound formulas Definition (PL): A well formed formula in the propositional logic is defined as follows: 1. Every basic proposition is a formula 2. If P is a formula, then P is a formula 3. If P and Q are formulas, then (PQ), (PQ), (PQ), (PQ) are formulas 5

6 Semantics P is true if P is false, and false if P is true. (PQ) is true if both P and Q are true and false, otherwise. (PQ) is true if P or Q is true and false, otherwise. (PQ) is true if P is false or if both P and Q are true and false, otherwise. (PQ) is true if P and Q are both true or false, and false otherwise. Interpretation of PL formulas Definition (Interpretation): Given a propositional formula G with atoms A 1,..,A k occurring in G. An interpretation of G is an assignment of truth values to A 1,..,A k in which every A i is assigned either T or F, but not both. Definition: A formula G is said to be true under an interpretation iff G is evaluated to T in the interpretation. Otherwise, G is said to be false under the interpretation. Definition (Model): Given a formula G and an interpretation I. If G is true under I, then I is called a model (for G). Checking validity and consistency of PL formulas Use truth tables! Definition (valid): A formula G is said to be valid iff it is true under all its interpretations. Definition (consistent, satisfiable): A formula G is said to be consistent (satisfiable) iff there is at least one interpretation under which G is true. Some remarks A valid formula G is said to be a TAUTOLOGY, e.g., G. An inconsistent formula G is said to be a CONTRADICTION, e.g., G. A valid formula is consistent but not vice versa. An inconsistent formula is invalid but not vice versa. Logical consequences Definition (Consequence): Given a formula F and G. G is said to be a logical consequence of F iff for any interpretation I in which F is true, G is also true. We write in this case F G. Some theorems Theorem 1: F G iff (FG) Theorem 2: F G iff (F G) is inconsistent Remark: If F G, then every model for F is also a model for G. 6

An example Given that if the congress refuses to enact new laws, then the strike will not be over unless it lasts more than one year and the president of the firm resigns, will the strike not be over

7 An example Given that if the congress refuses to enact new laws, then the strike will not be over unless it lasts more than one year and the president of the firm resigns, will the strike not be over if the congress refuses to act and the strike just starts? Abduction Another form of reasoning Given a theory and observations. Abduction tries to find an explanation for the observations which comes from the theory. Example: Theory: T ={ raining wet } Observation: O = { wet } Explanation: E = { raining }! T E O and T E is consistent Abduction Another example References What happens with our bird example? birds can fly penguins are birds tweety is a bird tweety is a penguin penguins cannot fly Possible explanations for the observation that penguins cannot fly are not consistent with the theory! (Try it) Chang and Lee, Symbolic Logic and Mechanical Theorem Proving, Academic Press, Bauer and Wirsing, Elementare Aussagenlogik, Springer-Verlag, R. Stoll, Set theory and logic, Dover, R. Smullyan, First-order logic, Dover, PL Example Constructed Wetlands Used in smaller villages to clean their waste water. 7

8 Problem description Modelling / Assumeables The weather, the position of the in valve, and the membrane have an impact on the water level. The water level impacts the plants. The nitrates and phosphates in the water have an impact on the plants. Weather Plants In valve Membrane Position of the input valve: VALVE Quality of the water coming in: WQUALITY Weather condition: WEATHER Condition of the Membrane: MEMBRANE Modelling / Facts, Observables Water level: ok_level Water quality: ok_np Weather: ok_weather Plants color: green, yellow Membrane: not_leaking Input valve: nom_inflow Model VALVE nom_inflow. MEMBRANE not_leaking. WQUALITY ok_np. WEATHER ok_weather. nom_inflow not_leaking ok_weather ok_level. ok_np ok_level green. green yellow. Problems with standard logics AI objectives Commonsense reasoning Bird example Explanations from theories Constructed wetland Nixon example The solution is Theory Formalize knowledge such that a machine can fulfill a certain task like a human. Find explanations Retain consistency Explain human intelligence 8

mywbut.com Introduction to AI

mywbut.com Introduction to AI Introduction to AI 1 1.1.1 Definition of AI What is AI? Artificial Intelligence is concerned with the design of intelligence in an artificial device. The term was coined by McCarthy in 1956. There are