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Market-Driven Multi-Agent Collaboration in Robot Soccer Domain Presented by Barış Kurt Outline What is a Market-Driven Strategy? How it works? Different Implementations What is a Market-Driven Strategy? Ap pl ication of the basic properties of free market economy to increase the benefit

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Market-Driven Multi-Agent Collaboration in Robot Soccer Domain

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Market driven multi agent collaboration in robot soccer domain l.jpg

Market-Driven Multi-Agent Collaboration in Robot Soccer Domain

Presented by Barış Kurt


Outline l.jpg

Outline

  • What is a Market-Driven Strategy?

  • How it works?

  • Different Implementations


What is a market driven strategy l.jpg

What is a Market-Driven Strategy?

  • Application of the basic properties offree market economy to increase the benefit

  • Based on the basic assumption that maximizing individual profits will approximate global profit maximization

  • Used for multi-agent task allocation


How it works l.jpg

How it works?

  • There exists an overall goal of the team that an outside entity is assumed to offer a payoff

  • The goal is decomposed into smaller tasks and an auction is performed for each of them

  • For each task, agents offer their prices to the auctioneer

  • The bidder with the lowest offeredprice will be given the right of execution of the task


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Market-driven scenario


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Prices of Tasks: The Cost Functions

  • The prices that agents offer for tasks are the estimated costs for accomplishing that task

  • For example:

    Cattacker = M2*distBall + M2*distOppGoal


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Auction Mechanism In Cerberus 2005

if(playerNumber==minDistOwner&&playerNumber==minDistOwnerForOppGoal)

{

robotRole=RR_PRIMARY_DEFENDER;

}

elseif(playerNumber==minDistOwner)

{

robotRole=RR_SECONDARY_ATTACKER;

}

else if(playerNumber==minDistOwnerForOppGoal)

{

robotRole=RR_SECONDARY_ATTACKER;

}

else if(playerNumber==minDistOwnerToOwnGoal)

{

robotRole=RR_PRIMARY_DEFENDER;

}

else

{

robotRole=RR_SECONDARY_ATTACKER;

}


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Different Implementations

  • Centralized

  • Distributed

  • Hybrid?


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Centralized Implementation

  • There exists a master agent (auctioneer) that controls the auctions and assigns the roles.

  • The master agent receives offers from all other agents for each task and sends the auction results back.

  • Computationally efficient.

  • Prone to single point failures.


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Distributed Implementation

  • No master agent.

  • Every agent broadcasts its offer for every task.

  • Every agent runs the same auction mechanism and parallely computes the auction results.

  • Robust against single point failures

  • Requires more computation in total.


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Hybrid Implementation

  • There exists a master agent

  • There is also an auction for the task of being the master

  • Robust against single point failures

  • Computationly efficient

  • Still not implemented, no test results.


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Thanks..

  • Questions?


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