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P2P Distributed Artificial Intelligence Matthieu Weber ([email protected]), 2007 Framework • P2P network of software agents • Agents are customers, workers and/or forwarders • Customers submit a job to the network, forwarders look for a suitable worker, workers perform the task • Experimenting different strategies • Trying to optimize the activities of the agents • Using simple economic models Matthieu Weber/University of Jyväskylä/Distributed Systems Research Seminar/2007-03-21 1 Possible Economic Models (1) • Secrecy: agents keep some part of their internal state secret • Money: forwading and task completion means money income, agents try to increase their wealth • Added value: wealth coming from outside of the system • Discounts: forwarders of large amounts get lower prices • Time limitation: processing prevents the node to do anyting else Matthieu Weber/University of Jyväskylä/Distributed Systems Research Seminar/2007-03-21 2 Possible Economic Models (2) • Bankruptcy: agents that cannot pay for new tasks disappear • Taxation: income is taxed (linearly or not) and evenly redistributed • Social policy: bankrupt agents can get social funding • Agent specialisation/diversification: agents become able to perform more or less kinds of tasks Matthieu Weber/University of Jyväskylä/Distributed Systems Research Seminar/2007-03-21 3 Possible Goals • Increase the wealth of individual agents • Increase the wealth of the whole system • Favorise specialisation or genericity Matthieu Weber/University of Jyväskylä/Distributed Systems Research Seminar/2007-03-21 4
