Welfare Engineering in Practice
ESAW 2004
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
Welfare Engineering in Practice
ESAW 2004
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
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
Talk Overview
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•
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Welfare Engineering
Designer scope
Resource Allocation Framework
Example Applications
Criteria
Conclusion
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
Welfare Engineering
How we can make agents negotiate socially
optimal outcomes?
Socially optimal allocation of resources
• Social welfare ordering (quality of the solution)
• Social interaction mechanism (to arrive at a solution)
• Behaviour profiles (interaction mechanism)
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
Talk Overview
•
•
•
•
•
•
Welfare Engineering
Designer scope
Resource Allocation Framework
Example Applications
Criteria
Conclusion
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
The Problem of the Designer Scope
Which agent does designer control?
• [Wurman et al 02]
Agent
• Agent scope
• Mechanism scope
• System scope
• Proprietor role
• End-user role
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
Talk Overview
•
•
•
•
•
•
Welfare Engineering
Designer scope
Resource Allocation Framework
Example Applications
Criteria
Conclusion
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
Resource Allocation by Negotiation
• Finite set of agents A and finite set of discrete resources R
• An allocation A is a partitioning of R amongst the agents in A
• Every agent i  A has a utility function ui(A)
u2(A)
u1(A)
2
1
R
A
A
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
u4(A)
u3(A)
3
4
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Welfare Engineering in Practice
ESAW 2004
Social Welfare
Majoring the well being of a society
• Egalitarian social welfare
Social welfare is tied to the welfare
of a society’s weakest member
• 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
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
Our framework (1/2)
• Monetary payments
– Deal couple with monetary side payment
– Payment function
• Limited money
• Approximating flows
– Representation of continuous resources (water,
energy, …)
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
Our framework (2/2)
• Roles
– Sellers
– Buyers
–…
• Protocol restrictions
– Restrictions on the negotiation protocol
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
Talk Overview
•
•
•
•
•
•
Welfare Engineering
Designer scope
Resource Allocation Framework
Example Applications
Criteria
Conclusion
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
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
?
?
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
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
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
Examples of Applications (2/3)
• Allocation of satellite resources [Lemaitre et al 03]
Agents
send observation request
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
Resources
initially held by the virtual proprietor
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Welfare Engineering in Practice
ESAW 2004
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
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
Talk Overview
•
•
•
•
•
•
Welfare Engineering
Designer scope
Resource Allocation Framework
Example Applications
Criteria
Conclusion
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
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
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
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
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
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
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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Welfare Engineering in Practice
ESAW 2004
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.
Y. Chevaleyre, U. Endriss, S. Estivie, N. Maudet
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