Optimization with Zeroth-Order Oracles in Formation

Elad Michael, Daniel Zelazo, Tony A. Wood, Chris Manzie, Iman Shames

Research output: Working paperPreprint


In this paper, we consider the optimisation of time varying functions by a network of agents with no gradient information. The proposed a novel method to estimate the gradient at each agent's position using only neighbour information. The gradient estimation is coupled with a formation controller, to minimise gradient estimation error and prevent agent collisions. Convergence results for the algorithm are provided for functions which satisfy the Polyak-Lojasiewicz inequality. Simulations and numerical results are provided to support the theoretical results.
Original languageEnglish
StatePublished - 30 Jul 2020


  • eess.SY
  • cs.SY


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