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Mobile Environmental Knowledge Assistant. Pierre MARET and Ken SASAKI, University of Tokyo. Pervasive environment. Autonomous players Intensive communication task No centralization Open environment: new players / players leaving without global impact Peripherics Personal assistants

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Mobile Environmental Knowledge Assistant


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mobile environmental knowledge assistant

Mobile Environmental Knowledge Assistant

Pierre MARET

and Ken SASAKI, University of Tokyo

pervasive environment
Pervasive environment
  • Autonomous players
  • Intensive communication task
  • No centralization
  • Open environment: new players / players leaving without global impact
  • Peripherics
    • Personal assistants
    • Sensors (wearable and fixed)

Lyon – 28 juin 2006

multi agent approach
Multi-agent approach
  • Each player is an agent
  • Compliance with pervasive systems
    • Autonomy
    • Intensive 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

virtual knowledge communities
Virtual Knowledge communities
  • Agents are provided with a layer for acting within knowledge communities
  • Knowledge community:
    • a leader + a topic
    • dynamic, no concrete existence, extends the topic
    • Related actions: create, join, inform, request, leave..
  • Exchanges are based on contents
  • Example
    • A: 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

agents in pervasive environment
Agents in pervasive environment

In our approach

  • User-oriented peripherics are associated to Personal Agents
  • Sensor are associated to Context Agents
  • Communications occurs within Virtual Knowledge Communities

Lyon – 28 juin 2006

general architecture
General architecture

Lyon – 28 juin 2006

example wake me up scenario
Example : Wake-me-up! scenario
  • Sensor: foot pressure

Context agent produces knowledge: user’s activity level

  • Environmental signal delivery into a metro station

Context 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

example wake me up scenario1
Example : Wake-me-up! scenario

Foot pressure sensor

Wake up the user if necessary

Metro station

Community on “station name”

Community on “activity”

Personal assistant

Lyon – 28 juin 2006

advantages
Advantages
  • Application design is made easier
    • Agents are made independently
  • New applications appears with new contents
  • System is open-ended and compliant with pervasive systems

Issues

  • Semantic heterogeneity: normalized ontologies, acquisition of semantic translators, …
  • Communication constraints, security, privacy…

Lyon – 28 juin 2006