Decentralised decision making in heterogeneous teams using anonymous optimisation

George M. Mathews*, Hugh Durrant-Whyte, Mikhail Prokopenko

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

27 Citations (Scopus)


This paper considers the scenario where multiple autonomous agents must cooperate in making decisions to minimise a continuous and differentiable team cost function. A distributed and asynchronous optimisation algorithm is presented which allows each agent to incrementally refine their decisions while intermittently communicating with the rest of the team. A convergence analysis provides quantitative requirements on the frequency agents must communicate that is prescribed by the structure of the decision problem. In general the solution method will require every agent to communicate to and have a model of every other agent in the team. To overcome this, a specific subset of systems, called Partially Separable, is defined. These systems only require each agent to have a combined summary of the rest of the team and allows each agent to communicate locally over an acyclic communication network, greatly increasing the scalability of the system.

Original languageEnglish
Pages (from-to)310-320
Number of pages11
JournalRobotics and Autonomous Systems
Issue number3
Publication statusPublished - 31 Mar 2009
Externally publishedYes


  • Asynchronous optimisation
  • Multi-agent systems
  • Team decision making


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