An Intelligent Agent-based Architecture An Intelligent Agent-based Architecture for Internet Mapping and Distributing for Internet Mapping and Distributing

Geographic Information ServicesGeographic Information Services

By Ming-Hsiang Tsou

E-mail: mtsou@mail.sdsu.eduPhone: 619-5940205

Fax: 619-5944938

AAG 2002, Los Angeles

The Department of Geography, San Diego State University

The Promise of Internet Mapping The Promise of Internet Mapping

Flexible Information Access/Distribution(Spatial Information at your fingertips + Real time data)

Information Sharing and Integration(Access multiple Internet map servers at the same time – local

data, federal agencies, USGS, EPA, Census etc.)

Distributed Mapping/GIS Tools: Web Services(LEGO-like GIS components/mapping tools)

3D, Visualization, Networking Analysis, Hydrological models

The Network is Your Mapping Factory The Network is Your Mapping Factory

Problems in Internet MappingProblems in Internet Mapping

Temporary, technology-centered solutions:

The lack of an intelligent architecture which can

operate in complicated mapping situations and

new/unknown environments.

Focus on Databases, not on Map Presentation:

We need to create a new mechanism for

connecting cartographic knowledge with Internet

mapping applications.

Information OverloadInformation Overload Access hundreds of map layers from different servers

How to combine Map-Server-A layersWith Map-Server-B layers?

Change Symbols? Apply Color Scheme?

Create scale threshold?

Use Different Projections?

Web Map Users Don’t Have Web Map Users Don’t Have Sufficient Cartographic KnowledgeSufficient Cartographic Knowledge

Current Web Maps:

•Good Interactivity•Good Flexibility

•Poor Quality•Poor Design

Web Map Users ≠ GIS Users

Possible Solution: Possible Solution: Intelligent Software AgentsIntelligent Software Agents

Apply cartographic principles to web mappingSoftware Agents (Cartographers pre-defined)+User defined rules

Establish cartographic rules dynamically (Different tasks have different rules and knowledge base)

Create distributed cartography knowledge base (CKB) (Access/Distribute different rules and symbols, color schemes, layout.. via the software agent network)

Software Agents

• Info. finders/filters• Interpreters • Decision makers

User-defined rules Cartography Knowledge Bases

Agent collaboration

Agent-based CommunicationAgent-based Communication

GIS Components(Programs)

GeodataObjects

Metadata Metadata

Design

Information Finder / FilterInformation Finder / Filter

Information Finder------------------------Information Filter

Carto-rulesRule-2Rule-3~ ~ ~ ~ ~Rule- 4

Color-scheme = DEMIso-line rulesInterpolation Algorithm

KEYWORDS(User-defined rules)

UsersColor SchemeLanduse-colorDEM-color~ ~ ~ ~ ~Zoning-color

Site-B

Site-A

GeneralizationMethod-1Method-2~ ~ ~ ~ ~Method-400

Site-C

Examples: Search “Color Scheme” for Digital Elevation Model.

Search Methods:1. Message Broadcasting 2. Agent Roaming3. Create a “Metadata Repository” to improve the search efficiency

Information InterpreterInformation Interpreter

Data-1 (UTM)

Metadata

[Buffering] in UNIX

Information Interpreter

Metadata

[Address matching] in Window 2000

Metadata

Data-2 (SPCS)

Metadata

Data-3 (Lat/Lon)

Metadata

Metadata becomes the source of knowledge bases

• Automatically convert from “UTM” coordinate systems to “SPCS California VI” by accessing the metadata of GIS data objects.

• Transform map units from feet to meters.

• Transform data from ESRI Shapefiles to AutoDesk SDFs.

The Design of Operational MetadataThe Design of Operational Metadata

Map display component

GIS-operation requirements (A, B)

System metadata

OtherGIS components

GeoData Object

Metadata(A, B, C, D, E, F)

Metadata describe how the Metadata describe how the objects should be represented objects should be represented (color, symbols) and the (color, symbols) and the domain of the object (vector, domain of the object (vector, line, transportation).line, transportation).

Integrating

Self-describing, Self-managingmap layers

Agent(decision maker)

Decision MakerDecision Maker

Events Actions

Agent(Information Finder)

Agent(Information Interpreter)

Agent Collaboration

•Event: If a new [polygon] data layer is added into point data layers.

•Agent Collaboration: •Info. Finder --> search for cartographic rules •Interpreter --> convert cartographic rules into executable procedures.

•Action: Move [point] data layers above the polygon layer.

Software Agents

Software Agents

User-defined rules(Cartographic rules)

Task #1 (Client Machine–A)

(Working memory)Task #2 (Client Machine–B)

(Working memory)

GIS data and components framework

GIS Component(Buffering)

Metadata(Facts)

GIS data object(Road, Colorado)

Metadata(Facts)

User Interface

Inference engine

Rules Facts Working memory

Traditional Traditional Expert SystemsExpert Systems

Intelligent software agentIntelligent software agent

Generalization

Hierarchy of GeoAgentsHierarchy of GeoAgents

GeoAgent

Machine Agent

Component Agent

Geodata Agent

UML notations

Stationary GeoAgent

Mobile GeoAgent

UML: Unified Modeling Language

Carto Agent

Walk-through Example Walk-through Example

Sd_pointofinterestMetadata:•Carto-Type: Point•Symbols: star•Color: red•Size: 7 point •Scale threshold: 1:20,000- 1:10,000

Carto Agents retrieve the operational metadata from data objects and apply it on the map design.

Dynamic Cartographic DesignDynamic Cartographic Design

Carto Agents re-arrange the layer sequences and reassign new color scheme for the landuse layer

Add a new landuse layer (metadata: color = blue)• Conflict with current sd_conven layer (same color: blue)• Overlap other information

Cartography OntologyCartography Ontology(Cartography Knowledge Base – CKB ) (Cartography Knowledge Base – CKB )

Statements:All point layers should be above all polygon layers.

First-Order Logic:

Computer Program: number layout sequences (1:top, 2:second..)

polylayer(x).number = i pointlayer(y).number = jIf (i < j) then {

polylayer(x).number = jpointlayer(y).number = i}

yx, Above( PointLayer(x), PolyLayer(y) )

Combining Metadata and Rules Combining Metadata and Rules

Cartographic Rule:If the color of the new polygon layer is the same as one of the existing layers, carto-agents will change the color of new layer to a unique color.

Computer Program:Color[AllPolyLayers] = [blue, red, green]Color(NewLayer) = NewLayer.metadata.color

While ( Color[AllLayers] contain Color(NewLayer) ) { Color(NewLayer) = Color(Randam) }

Inference by Multiple Knowledge Bases Inference by Multiple Knowledge Bases

Multiple Cartographic Knowledge Bases (CKB):•Rule#1: “Landuse” data objects are qualitative. (from San Diego State University) http://map.sdsu.edu/001.ckb•Rule#2: Color-hue is best visual variable for displaying qualitative area data. (from UC-Santa Barbara) http://geog.ucsb.edu/hydro.ckb)

Inference:Rule#1 AND Rule#1 Landuse should use “Color-hue” for area symbol display.

Computer Program (Software Agents):Landuse.Symbols =

ColorScheme(Hue).Attribute(LU)

GIServices Workstation (a GIS node)

Agent Container

GIS Component Container

GeoData Object Container

Machine Agent

Hardware Profiles: CPU, OS, CRT, printer, scanner

Component Agent GeoData Agent

M M M M

M : metadata

M M

Implementation: GIService NodeImplementation: GIService Node

Carto Agent

Software Agent PlatformSoftware Agent Platform

• Java (Sun Microsystems): Java Virtual Machine (VM), Java applets / servlets.

• CORBA (OMG): Common Object Request Broker Architecture, UNIX-based, IIOP (Internet Inter-ORB Protocol),

• .NET (Microsoft): Windows 2000/NT, ActiveX container, COM-based model

• XML (W3C): (Extensible Markup Language)lightweight agent systems, scripting language, open-ended, metadata- enhanced.

Agent Communication Agent Communication Language (ACL) / Protocol (ACP)Language (ACL) / Protocol (ACP)

• KQML (Knowledge Query and Manipulation Language) (Finin and Weber, 1993)

•ACL (Agent Communication Language) specification FIPA (Foundation for Intelligent Physical Agents) 1997

• IIOP (Internet Inter-ORB Protocol), and CORBA’s Mobile Agent Facility Specification 1.0

OMG, (1999)

• XML-based scripting language (Lange, Hill, & Oshima, 2000)

Current Internet MappingCurrent Internet Mapping

Intelligent Agent SolutionIntelligent Agent Solution• Improve the quality of web maps• Create dynamic cartographic design• Search for appropriate map styles / color schemes.• Establish distributed cartographic knowledge bases.

• Poor quality of maps - No cartographic principles• Problems with multiple data/layer presentation• Difficult to apply color schemes / map styles• Unknown situation for mapping new data objects

SUMMARYSUMMARY

FUTURE WORKFUTURE WORK

Implementation of Cartography OntologyConvert from “logics and rules” to “computer languages”

New Cartographic Principles for New Tasks3D rules, Layer Transparency, Animation rules, etc.

Other A.I. possibility for software agents?Fuzzy logic for scale threshold?,

Probabilistic theory for Data uncertainty representation? Neural networks for _______???,

PowerPoint Slide is available: http://map.sdsu.edu