Outline Administrative issues Course overview What are Intelligent Systems? A brief history State of the art Intelligent agents

Course overview I.Introduction IS II.Intelligent agents III.Search IV.Knowledge and reasoning V.Planning VI.Uncertainty VII.Learning VIII.Hybrid systems

Course overview I.Introduction IS II.Intelligent agents III.Search IV.Knowledge and reasoning V.Planning VI.Uncertainty VII.Learning VIII.Hybrid systems

What is an Intelligent System? System that: does everything that I want it to do & nothing that I don’t Human-like reasoning recover from failure Learns from its mistakes Adapts to its environment Makes decision about appropriateness of actions

What are Intelligent Systems? (What is AI?) Systems that think like humans rationally Systems that think rationally Systems that act like humans rationally Systems that act rationally Turing test Cognitive science Logic Agents

Turing test (‘50)

Turing test pro’s & cons Predicted that by 2000 a machine might have a 30% chance of fooling a lay person for 5 min Anticipated major arguments against AI –Pb: not reproducible, constructive, allows no mathematical analysis Suggested major components of AI: knowledge, reasoning, language understanding, learning

Acting rationally Doing the right thing Expected to maximize goal achievement, given available info Doesn’t necessarily involve thinking!! –Reflexes, etc.

Dimensions of AI 1.symbolic or sub-symbolic (i.e., numerical) 2.manually engineered or automatically learned 3.cognitively plausible 4.perfect world assumption or probabilistic 5.evaluated by hunch, single example, authoritative tone of voice or numerical measure 6.classification, numerical or planning 7.full system or human-assistor 8.online or offline 9.real-time or offline 10.intelligent or just software engineering 11.sound theoretical foundation or trial&error

(some) Categories of intelligent system software All software KnowledgebasedsystemsComputationalintelligence NN Evolutionary alg. Simulated Annealing Objects, frames, agents Rule based systems Expert systems Bayesian updating, Certainty theory, Fuzzy logic

Example: intelligent agent Steve Acting rationally + humanly Collaboration

Example: evolution Evolving artificial creatures, Karl Sims:

Other Intelligent Systems Distributed intelligence

Applications of Intelligent Systems

Applications of Adaptive Systems expert systems –(e.g. medical diagnosis) data mining –(e.g. search engines) computational linguistics games

More Applications Parallel computing: –evolution of cellular automata Molecular biology: –molecular evolution, design of useful molecules, protein design Computer security: –immune systems for computers Intelligent agents and robotics – Internet!! Scientific modeling: –evolution, ecologies, economies, insect societies, immune systems, organizations

AI is New Science We're still learning about perceiving, planning and learning It is hard to compare methods/paradigms I'm you're tour guide: methods and applications You'll be pointed at research + literature

Should we replace people with machines? Yes. Expand the meaning of "grunt-work", and make a machine do it. No. The devastating dehumanisation of automation. No. Economic objections? No. A National Aeronautics and Space Administration report supporting manned space exploration states, "Man is the lowest cost, 150-pound, non-linear, all-purpose computer system that can be mass produced by unskilled labour." –with built-in sense-of-humour system Yes. what about the expense of life support and litigation? No. Nothing's gonna replace people; I'm a humanitarian

Course overview I.Introduction IS II.Intelligent agents III.Search IV.Knowledge and reasoning V.Planning VI.Uncertainty VII.Learning VIII.Hybrid systems

II. Intelligent agents Rational agent: generalities Agent & its environment Example: a simple agent Rationality defined Task environment: –PEAS –Proprieties Agent proprieties