Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. Market-based Risk Allocation for Multi-agent Systems

Market-based Risk Allocation for Multi-agent Systems

Thumbnail Image
Download
Name

Williams_MarketBased.pdf

Size

396.26 KB

Format

Adobe PDF

Checksum (MD5)

0a32e527372388a0dfc5d90f152dc2c3

Author(s)
Ono, Masahiro
•
Williams, Brian Charles
Date Issued
May 2010
Journal
Proceedings of the Ninth International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2010
Publisher
Association for Computing Machinery
Citation
Ono, Masahiro and Brian C. Williams. "Market-based Risk Allocation for Multi-agent Systems." In Proceedings of the Ninth International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2010, Toronto, Canada, May 10-14, 2010.
Version
Author's final manuscript
Abstract
This paper proposes Market-based Iterative Risk Allocation (MIRA), a new market-based distributed planning algorithm for multi-agent systems under uncertainty. In large coordination problems, from power grid management to multi-vehicle missions, multiple agents act collectively in order to optimize the performance of the system, while satisfying mission constraints. These optimal plans are particularly susceptible to risk when uncertainty is introduced. We present a distributed planning algorithm that minimizes the system cost while ensuring that the probability of violating mission constraints is below a user-specified level. We build upon the paradigm of risk allocation (Ono & Williams 2008), in which the planner optimizes not only the sequence of actions, but also its allocation of risk among each constraint at each time step. We extend the concept of risk allocation to multi-agent systems by highlighting risk as a commodity that is traded in a computational market. The equilibrium price of risk that balances the supply and demand is found by an iterative price adjustment process called tˆatonnement (also known as Walrasian auction). Our work is distinct from the classical tˆatonnement approach in that we use Brent’s method to provide fast guaranteed convergence to the equilibrium price. The simulation results demonstrate the efficiency of the proposed distributed planner.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Attribution-Noncommercial-Share Alike 3.0 Unported
http://creativecommons.org/licenses/by-nc-sa/3.0/
Persistent DSpace Link
http://hdl.handle.net/1721.1/67892
DOI of Published Version
http://www.cse.yorku.ca/AAMAS2010/index.php#content=accepted_papers
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.