1 / 10

NEW TIES year 2 review

NEW TIES year 2 review. NEW TIES = N ew and E mergent W orld models T hrough I ndividual, E volutionary and S ocial learning. Timetable. 10.00 – 10.20 Coordinator’s opening and summary 10.20 – 10.45 WP1 presentation: scenarios and challenges

santiago
Download Presentation

NEW TIES year 2 review

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. NEW TIES year 2 review NEW TIES = New and Emergent World models Through Individual, Evolutionary and Social learning

  2. Timetable • 10.00 – 10.20 Coordinator’s opening and summary • 10.20 – 10.45 WP1 presentation: scenarios and challenges • 10.45 – 11.15 WP2 presentation: evolving NEW TIES agents 11.15 – 11.30 Coffee break • 11.30 – 12.00 WP3 presentation: language evolution and communication • 12.00 – 12.30 WP4 presentation: data analysis tools • 12.30 – 13.00 WP5 presentation: distributed NEW TIES platform 13.00 – 14.00 Lunch break • 14.00 – 14.20 WP6 presentation: integration & evaluation • 14.20 – 14.50 Questions and answers session • 14.50 – 15.30 Review panel: deliberation (incl. coffee), project participants: coffee break • 15.30 – 16.00 Review panels feedback to project participants

  3. What is NEW TIES? An artificial agent world with • Interesting scenarios / challenges • Emergence engine = • Evolutionary learning • Individual learning • Social learning • Language evolution — link with IL & SL • Detection of world models (culture, data mining) • Large scale: many & complex agents, long simulations

  4. Main objectives from Annex I • To develop an artificial society with an emergent culture. • To realise a powerful “emergence engine” as a combination of individual learning, evolutionary learning, and social learning. • To develop, evaluate, and use a range of social learning mechanisms that allow sharing knowledge with other members of the population. Essential & distinguishing feature: enormous scale-up

  5. NEW TIES questions (examples) • Can a NT society learn “ecologically correct” behavior? • Can individual learning compensate for bad genes? And social learning? • Can the agents develop language and share info through it? Can we understand it? • Will telepathy work as social learning mechanism? • What culture will emerge? • Can we start a (p2p) SIG where users compete by their “home-brewed tribes” in a NT world? Could we win such a competition?

  6. Agents Language Learning Environment New Ties Virtual Machine Visualisers Data Miners Modular Design

  7. Simulated world WP1: environment & challenges WP5: p2p infrastructure WP2: agents and learning WP3: language, communication, cooperation WP4: emerging world models WP6: integration and evaluation Project structure (tech part)

  8. Year 2 in brief • Major code restructuring  effective start of NEW TIES experiments in April-May 2006 • Experiments: • Evolutionary learning: • simple world (calibration) and • poison world (challenge solved) • Language evolution: collective lexicon developed • Development: • Scenario generator • World model detectors, data analysis (user in the loop!) • Distributed platform

  9. Main achievements per WP • WP1: Scenario generator and map viewer • WP2: Evolutionary learning in NEW TIES • WP3: Language evolution in NEW TIES • WP4: Interactive data analysis tools • WP5: Distributed platform beta, incl. historical data module • WP6: Complete code restructuring • WP7: Release of the NEW TIES platform

  10. Biggest challenges at the moment • Evolution remains the only learning mechanism, i.e., no IL and no SL • Evolved language (components) not used by agents for info exchange or as building blocks in IL • Simulation times are too long • No challenging and appealing scenario solved NEW TIES must become more than another ALife project

More Related