Artificial Intelligence Universitatea Politehnica Bucuresti Adina Magda Florea

L1 – Course content Introduction to AI Search techniques Symbolic logic Theorem proving. Prolog Rule based systems Partial exam - 1 h Frame based systems Uncertain reasoning Automatic planning Machine learning Natural laguage understanding Final exam - 3h Knowledge representation Aplications

Course materials Books A. Florea, A. Boangiu. Elemente de Inteligenta Artificiala. A. Florea. Bazele logice ale Inteligentei Artificiale. Cap. 4, 6. A. Florea, S. Radu, A. Mogos. Tehnici de programare Prolog pentru inteligenta artificiala – in print On-line articles "Computing Machinery and Intelligence", Turing, A.M. Mind, 59, 1950, "AI's Greatest Trends and Controversies", IEEE Intelligent Systems January/February "A Framework for Representing Knowledge", Marvin Minsky, MIT-AI Laboratory Memo 306, June, 1974.

Requirements Laboratory: min 6 Laboratory homework Partial exam Final exam Grading Partial exam: 20% Final exam: 50% Laboratory: 30%

Lecture No. 1 What is artificial intelligence Features of AI problems History Structure of an AI system AI domains

Key questions Is it possible to make computers intelligent? How can we determine if a computer program is intelligent? At what level do we model intelligent behavior? Which representations and which techniques do we use in AI?

1. What is Artificial Intelligence Alan Turing - “Computing Machinery and Intelligence”, 1950 Simulation of human intelligence Emulation of human intelligence Symbolic AI Computational Intelligence AI Definitions

2. Features of AI problems General Dynamics Difficult (complexity) Knowledge vs data Heuristic knowledge, common sense Uncertain knowledge Reasoning, inferences Autonomy Learning/adaptation

Inferences Inference Rule of inference Inference strategy Complete / incomplete Consistent (sound) / Inconsistent (unsound)

Examples of Inference Rules A Deductive inferences A  B B nice(john) Nondeductive inferences nice(tom)  x nice(x) Modus ponens Inductive inference

3. History Conference - Dartmouth College 1956 – AI - John McCarthy, Marvin Minsky, Alen Newell, Herbert Simon A. Newell, J. Shaw si H. Simon - "The Logic Theorist." 1960 AI programs 1965 J. A. Robinson – resolution 1965 – DENDRAL - J. Lederberg si E. Feigenbaum. – expert system Lisp (LISt Processing) - John McCarthy (Dartmouth College) Prolog (PROgrammation et LOGique) - Alain Colmerauer (universitatea Marseille-Aix) Smalltalk - Goldberg, Robson

History ’70 – knowledge Knowledge based systems Knowledge engineering MYCIN - Buchanan, Shortliffe - Stanford University - '74- '75 Expert systems Expert systems shells ’80-’90 – disappointment ’90-’00 – interest, lot of research DAI IA and MAS Intelligent components, inteligent behavior Semantic Web

4. Structure of an AI system Interaction with the environment Intelligent system Perception Action

Structure of an AI system Interaction with the environment Knowledge base Inference engine Control strategy User interface Knowledge acquisition

5. AI domains Knowledge representation, ontologies Common sense reasoning Games Automatic theorem proving Planning techniques Knowledge acquisition Machine learning NL processing Perception Expertise in specific domains Intelligent agents Multi-agent systems

16 Buttler agent Imagine your very own mobile butler, able to travel with you and organise every aspect of your life from the meetings you have to the restaurants you eat in. The program works through mobile phones and is able to determine users' preferences and use the web to plan business and social events And like a real-life butler the relationship between phone agent and user improves as they get to know each other better. The learning algorithms will allow the butler to arrange meetings without the need to consult constantly with the user to establish their requirements.

17 Robocup agents The goal of the annual RoboCup competitions, which have been in existence since 1997, is to produce a team of soccer-playing robots that can beat the human world champion soccer team by the year

18 True UAV Autonomy In a world first, truly autonomous, Intelligent Agent-controlled flight was achieved by a Codarra ‘Avatar’ unmanned aerial vehicle (UAV). The flight tests were conducted in restricted airspace at the Australian Army’s Graytown Range about 60 miles north of Melbourne. The Avatar was guided by an on-board JACK™ intelligent software agent that directed the aircraft’s autopilot during the course of the mission.

19 ALICE robot Trading Agents Competition The Loebner Prize in AI AI Portal MONET Network of excellence