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

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Presentation on theme: "Outline Administrative issues Course overview What are Intelligent Systems? A brief history State of the art Intelligent agents."— Presentation transcript:

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

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

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

4 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

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6 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

7 Turing test (‘50)

8 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

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

10 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

11 (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

12 Example: intelligent agent Steve Acting rationally + humanly Collaboration

13 Example: evolution Evolving artificial creatures, Karl Sims:

14 Other Intelligent Systems Distributed intelligence

15 Applications of Intelligent Systems

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

17 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

18 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

19 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

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

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


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