Laboratoire d'InfoRmatique en Image et Systèmes d'informationINSA de Lyon

LIRIS UMR 5205 CNRS/INSA de Lyon/Université Claude Bernard Lyon 1/Université Lumière Lyon 2/Ecole Centrale de LyonUniversité Claude Bernard Lyon 1, bâtiment Nautibus

43, boulevard du 11 novembre 1918 — F-69622 Villeurbanne cedexhttp://liris.cnrs.fr

UMR 5205

ICPS 2006

Mobile Environmental Knowledge Assistant

Pierre MARET

and Ken SASAKI, University of Tokyo

Lyon – 28 juin 2006 2ICPS’06

Pervasive environment

Autonomous playersIntensive communication taskNo centralization Open environment: new players / players leaving without global impactPeripherics

Personal assistantsSensors (wearable and fixed)

Lyon – 28 juin 2006 3ICPS’06

Multi-agent approach

Each player is an agentCompliance with pervasive systems

AutonomyIntensive communication

Agents have two components (Agent Oriented Abstraction):

Knowledge: concept classes, instance, actions (that can be further specialized). = Ontology.

A decision mechanism (associated to utility function): for instance Evaluate a message, Send an Inform, …

Lyon – 28 juin 2006 4ICPS’06

Virtual Knowledge communities

Agents are provided with a layer for acting within knowledge communitiesKnowledge community:

a leader + a topic dynamic, no concrete existence, extends the topicRelated actions: create, join, inform, request, leave..

Exchanges are based on contents

ExampleA: creates a community on concept “Metro station name”B: decides to join the community and informs about

“Ginza”, instance of “Metro station name”

Lyon – 28 juin 2006 5ICPS’06

Agents in pervasive environmentIn our approach

User-oriented peripherics are associated to Personal AgentsSensor are associated to Context Agents

Communications occurs within Virtual Knowledge Communities

Lyon – 28 juin 2006 6ICPS’06

General architecture

Virtual Knowledge Community

Ontological-contextual data

Ontological-personal data

heritage from

Sensors

Context data

Context Agent

Context-aware personal assistant

Context-aware application

Sensors

Context data

Context Agent

Ontological-contextual data

Personal Agent

Lyon – 28 juin 2006 7ICPS’06

Example : Wake-me-up! scenario

Sensor: foot pressureContext agent produces knowledge: user’s activity

level

Environmental signal delivery into a metro stationContext agent delivers knowledge: station name

Personal assistant of traveler : Personal agent knows the desired station and a evaluation rule when to

wake-up the traveler (activity is low and desired station is reached)

is interested in “Activity level” and “Metro station names”

Lyon – 28 juin 2006 8ICPS’06

Example : Wake-me-up! scenario

Wake up the user if necessary

Virtual Knowledge Community

Ontological-contextual data

Ontological-personal data

heritage from

Sensors

Context data

Context Agent

Context-aware personal assistant

Context-aware application

Sensors

Context data

Context Agent

Ontological-contextual data

Personal Agent

Community on “station name”

Community on “activity”

Metro station Foot pressure sensor

Personal assistant

Lyon – 28 juin 2006 9ICPS’06

Advantages

Application design is made easierAgents are made independently

New applications appears with new contentsSystem is open-ended and compliant with pervasive systems

Issues

Semantic heterogeneity: normalized ontologies, acquisition of semantic translators, …

Communication constraints, security, privacy……