1 / 15

MASQUE Multi-Agent System for Supporting the Quest for Urban Excellence DDSS group presentation

MASQUE Multi-Agent System for Supporting the Quest for Urban Excellence DDSS group presentation 20/06/02. Dick Saarloos. Contents. Recall MASQUE Local Urban Planning Instruments Plan development process Complicating factors Computer Assistance in Urban Planning

randall-peck
Download Presentation

MASQUE Multi-Agent System for Supporting the Quest for Urban Excellence DDSS group presentation

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. MASQUEMulti-Agent System for Supporting the Quest for Urban Excellence DDSS group presentation 20/06/02 Dick Saarloos

  2. Contents • Recall MASQUE • Local Urban Planning • Instruments • Plan development process • Complicating factors • Computer Assistance in Urban Planning • Potentials and difficulties • Prospects of Artificial Intelligence • MASQUE Planning Support System • Organizational system parts • Multi-Agents • Implementation Issues

  3. MASQUE ~ Program & Project • Research program “Local Urban Planning Support System” • Improving quality of decision-making • Multidisciplinary knowledge representation • Models, methods and techniques • Applying Multi-Agent technology • Research project • MA Framework • Case study ~ usefulness of MA-PSS

  4. Instruments of Local Government • Planning instruments • Structure plan • Outline of overall urban development policy • Thematic plan • Development policy for a specific land-use • Land use plan • Legally-binding regulations for permissible land-use • Design instruments • e.g. (re)development plan • Arrangement of masses and spaces

  5. Urban Plan Development Process • Process phases (Rutledge, 1971) • Survey • Inventory • Program • Analysis • Site Analysis • Relationship Diagrams • Synthesis • Design Concepts • Plan Refinement & Finalization

  6. Complicating Factors • Procedural irregularities (Batty & Densham, 1996) • Iterations • Incompleteness & dilution • “Nature of the problem” (Yeh & Shi, 1999) • Complexity • Many interwoven factors and relationships • Uncertainty • Unclear cause-effect relationships • Situational factors • Subjectivity • Urge for creativity

  7. Computer Assistance • Core task in Local Urban Planning • “Find the optimal spatial configuration of land uses while taking into account both land suitability and land use characteristics.” • Basic potentials • Enumeration of alternatives • Multi-criteria evaluation • Needs • Multidisciplinary knowledge • Methodological tools

  8. Prospects of Artificial Intelligence • Planning Support System ~ ideal • GIS capabilities • Purpose-built decision support models • Visualization • Knowledge • Multi-Agents • Multi-actor decision-making • Modelling • User-System interaction

  9. MASQUE~ Organizational system parts • Inventory • Program • Analysis • Synthesis • Implementation • Monitoring (free after Rutledge, 1971)

  10. MASQUE Multi-Agent System Geographical Database Management System Model-Based Management System Dialogue Generation and Management System User MASQUE ~ System overview

  11. Interface Agents

  12. Tool Agents

  13. Domain Agents • Domains: Residential areas, Commercial areas, Transportation, Services, Landscape, Recreation, Technical infrastructure, Hydraulic constructions

  14. Implementation Issues • Software • MicroStation & MicroStation GeoGraphics • CAD & GIS functionalities • Java Agent DEvelopment Framework (JADE) • “Primitive” agent model and platform • No enforced agent architectures • Ready made behaviours for common agent tasks • Java Expert System Shell (JESS) • Define rule-based agent behaviours • Engine for executing behaviours

  15. The End

More Related