1 / 11

The Dream of an Intelligent Machine by Hans W. Guesgen

Explore the beginning of AI, inherited from philosophy, math, psychology, and more. Discover the gestation of AI, seminal works, great expectations, and the reality check of AI problems. Learn about knowledge-based systems, games like chess and checkers, intelligent agents, multi-agent systems, and related issues such as AI and emotions.

vincent-petty
Télécharger la présentation

The Dream of an Intelligent Machine by Hans W. Guesgen

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The Dream of an Intelligent Machine Hans W. Guesgen Computer Science Department

  2. The Beginning of AI • AI itself is a young field, but … • It has inherited from other disciplines: • Philosophy • Mathematics • Psychology • Computer engineering • Linguistics

  3. Gestation of AI • McCulloch and Pitts (1943): • Model of artificial neurons • Any computable function can becomputed by some network of neurons • Suitably defined neural networks can learn • Newell and Simon (Dartmouth, 1956) • Logic Theorist (LT)

  4. Great Expectations • Early successes: • Lisp • Microworlds • Simon (1957): • It is not my aim to surprise or shock you – but the simplest way I can summarize is to say that there are now in the world machines that think, that learn and that create. Moreover, their ability to do these things is going to increase rapidly until – in a visible future – the range of problems they can handle will be coextensive with the range to which human mind has been applied.

  5. A Dose of Reality • Many AI problems are intractable: • Combinatorial explosion • NP-complete • Solving problems often requires subject knowledge: • Translation from German into English • Finding a good route into the city during rush hour

  6. Knowledge-Based Systems • Closed-world assumption • Expertise in a limited field • Rule-based approach • Examples: • MYCIN • DENDRAL • PROSPECTOR • R1

  7. Games • Checkers (or draught): • Samuel’s checker program (1952) • Schaeffer’s program CHINOOK(won 1992 U.S. Open) • Chess • Kasparov vs.Deep Blue (1997)

  8. Intelligent Agents • New paradigm for AI systems: • Uses sensors toperceive theenvironment • Uses effectors toact upon thatenvironment • Uses planningto behave rational

  9. Multi-Agent Systems • Agents collaborating with each other • Distributed competence/intelligence • Emergent rather than individual intelligence

  10. Related Issues • AI and humanoid form • AI and emotions • AI and gender • AI and …

More Related