Unstructured Agent Matchmaking

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Unstructured Agent Matchmaking Experiments in
Timing and Fuzzy Matching
Elth Ogston and Stamatis Vassiliadis Computer
Engineering Laboratory TU Delft
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• Are there elements of coordination within large
  multi-agent systems that can be obtained for
  free? i.e.
• Without complicated agent algorithms (planning,
  scheduling, intelligence)
• Without external structure
• (facilitators, directories, blackboards, know
  topology)

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• Matchmaking how do agents that require an
  outside service find other agents who are willing
  to provide that service?
• Assume redundancy of providers and consumers
• (MAS are open, flexible and component based)
• Simple agents
• Coordination without outside help
• How studied? - Simulation of an abstract model.
• Results? - We find that there are conditions
  under which simple unaided agents do find matches
• This paper checking two further conditions,
  timing and how matches are determined

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Talk Organization

• General philosophy
• Overview of our model and previous results
• Some new results on timing and forms of matching
• Summary of further work

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Philosophy - scalability
Multi-agent systems can in theory be
world/internet size.
However they often make use of systems
components, like directories, that dont scale
well why?
Humans tend to believe in (central) control (God,
aliens, The FBI, Mom)
Scientists and engineers who design computers are
trained to see order in the world.
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Philosophy sloppy systems
Natural systems tend to be redundant and full of
failures. Lets try looking at coordination not
as beautifully interlocking clockwork but as an
cloud that just happens to look like an elephant
when you squint a bit, turn it upside down, and
ignore that part over there.
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Philosophy matchmaking thought experiment
Imagine a number between 1 and 10.
How would you find someone else in the room with
the same number?

• Broadcast

• Broker

• Ask your neighbors

Now scale up, find someone in Madrid with a
number between 1 and 100,000
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Model - Components
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Model -Movement
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Model - Characteristics

• There are several good matches available
• We arent looking for the global best match
• Not all agents need to be successful
• No centralized directory
• No predefined structure
• Agents are simple
• Agents only know about their immediate
  surroundings

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Previous Results

• Matches are found
• Limited by the number of task categories and the
  number of neighbors to each agent
• Limiting cluster size creates a distributed
  system
• Replacing tasks creates a dynamic system

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New Results

• System timing doesnt play a role in coordination
• Fuzzy probabilistic category matches produce the
  same behavior as discreet deterministic matches

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Agents moving in sync vs. agents moving in a
random order
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Deterministic matches vs. probabilistic matches
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Further Work

• AAMAS 2002 comparison of a peer-to-peer auction
  with a centralized auction
• P2P shows same auction behavior
• As we add more agents P2P has constant message
  costs vs. linear for a central auctioneer

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More Info.
http//ce.et.tudelft.nl/elth/