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Welfare Engineering in Practice: On the Variety of Multiagent Resource Allocation Problems

Welfare Engineering in Practice: On the Variety of Multiagent Resource Allocation Problems. Yann Chevaleyre 1 , Ulle Endriss 2 , Sylvia Estivie 1 and Nicolas Maudet 1. (1)LAMSADE, Univ. Paris IX-Dauphine (2)Dept. of Computing, Imperial College London. Introduction.

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Welfare Engineering in Practice: On the Variety of Multiagent Resource Allocation Problems

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  1. Welfare Engineering in Practice: On the Variety of Multiagent Resource Allocation Problems Yann Chevaleyre1, Ulle Endriss2, Sylvia Estivie1 and Nicolas Maudet1 (1)LAMSADE, Univ. Paris IX-Dauphine (2)Dept. of Computing, Imperial College London

  2. Introduction • Recurring problems like E-auctions, patrol … • Similarities between these problems ? Not exploited yet… • Formalize this similarities for a category of problem : Resource allocation problem • Why??? • A lot of theoretical result for resource allocation • Possibility to develop a platform

  3. Talk Overview • Welfare Engineering • Designer scope • Resource Allocation Framework • Example Applications • Criteria • Conclusion

  4. Welfare Engineering How we can make agents negotiate socially optimal outcomes? • Social welfare ordering (quality of the solution) • Social interaction mechanism (to arrive at a solution) • Behaviour profiles (interaction mechanism) Socially optimal allocation of resources

  5. Talk Overview • Welfare Engineering • Designer scope • Resource Allocation Framework • Example Applications • Criteria • Conclusion

  6. The Problem of the Designer Scope Which agent does designer control? • [Wurman et al 02] • Agent scope • Mechanism scope • System scope • Proprietor role • End-user role Agent

  7. Talk Overview • Welfare Engineering • Designer scope • Resource Allocation Framework • Example Applications • Criteria • Conclusion

  8. u2(A) u1(A) 2 1 R A u4(A) u3(A) 4 3 A Resource Allocation by Negotiation • Finite set of agents A and finite set of discrete resourcesR • An allocationA is a partitioning of R amongst the agents in A • Every agent i Ahas a utility function ui(A)

  9. Social Welfare Majoring the well being of a society Social welfare is tied to the welfare of a society’s weakest member • Egalitarian social welfare • Utilitarian social welfare • Anything that increases average utility • is taken to be socially beneficial • Envy-freeness social welfare • There is zero probability of having an • agent envying somebody else • Research issue : the impact of individual utility on social welfare

  10. Our framework (1/2) • Monetary payments • Deal couple with monetary side payment • Payment function • Limited money • Approximating flows • Representation of continuous resources (water, energy, …)

  11. Our framework (2/2) • Roles • Sellers • Buyers • … • Protocol restrictions • Restrictions on the negotiation protocol

  12. Talk Overview • Welfare Engineering • Designer scope • Resource Allocation Framework • Example Applications • Criteria • Conclusion

  13. ? ? Examples of Applications (1/3) • Multiagent Patrolling (1/2) • The multiagent patrolling problem: how should agents move around an area such that every part of the area is visited the most often ? • Goal : find strategies which minimize the time between 2 visit on each node

  14. Examples of Applications (1/3) • Multiagent Patrolling (2/2) • Multiagent patrolling applies to: • Multi-robot applications (intrusion detection, cleaning team of robots, delivery) • Video-games (in warcraft-like games, doom-like, …) • Military application (surveillance, tracking intruders) • Internet applications • Resources : each node • Utility of each agent : how well it patrols over the node it owns • Resource allocation : agent can exchange nodes in order to maximize his patrolling performance

  15. Examples of Applications (2/3) • Allocation of satellite resources [Lemaitre et al 03] Resources initially held by the virtual proprietor Agents send observation request

  16. Examples of Applications (3/3) • E-Auctions • Different kinds of e-auction • B2C (Business to Consumer) : antique dealer • C2C (Consumer to Consumer) : eBay like • B2B (Business to Business) : FCC, fairmarket… • Similarities and differences : but all could be represented with a model of resource allocation. • Roles : sellers and buyers

  17. Talk Overview • Welfare Engineering • Designer scope • Resource Allocation Framework • Example Applications • Criteria • Conclusion

  18. Criteria for a Social Welfare Selection (1/2) Proprietor gain • Utility-dependent • Example : tax on gain • Example of application uses it : Multiagent Patrolling • Transaction-dependent • Example : tax on each transaction • Example of application uses it : e-auctions • Membership-dependent • Example : Entrance fees • Example of application uses it : Satellite allocation, e-auctions

  19. Criteria for a Social Welfare Selection (2/2) Application dynamics Between a run • Possibility for an application to run several times • Yes : Satellite application, C2C e-auctions • No : FCC e-auctions • If yes, whether and how the characteristics could be modified between runs? • C2C e-auctions : users may be different

  20. Conclusion • Multiagent resource allocation : A powerful paradigm • The first idea of social welfare choice in not necessarily the better.[Guttman, Maes 99] Toward a test platform

  21. References • [Guttman, Maes 99] R.H. Guttman and P. Maes. Agent Mediated integrative negotiation for retail electronic commerce. In Agent Mediated Electronic Commerce, 1999. • [Lemaitre et al 03] M. Lemaitre, G. Verfaillie, H. Fargier, J. Lang, N. Bataille and J.M. Lachiver. Equitable allocation of earth observing satellites resources. In Proc of the 5th ONERA-DLR Aerospace Symposium (ODAS’03), 2003. • [Wurman et al 02] P.R. Wurman, M.P. Wellman, and W.E. Walsh. Specifing rules for electronic auctions. AI Magazine, 23(3):15-23, 2002.

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