ADAPTIVE DECENTRALIZED RESOURCE OPTIMIZATION

Abstract

In this project, we will develop algorithms in support of automated decentralized decisionmaking system that adapts to unknown changes in the surrounding environment. Problems of optimal decision-making among multiple agents can be formalized as adequate optimization problems. The major scientific challenge is that these optimization problems should not be solved in a centralized fashion, but rather, the agents themselves need to cooperate on a decentralized computation of the optimal decision and, furthermore, the agents have to repeatedly adapt and revise their decision as new information arrives. Our proposed work has objective to advance the state-of-the-art of distributed computations by tackling head-on the full complexity of the optimization. In particular, we will handle timevarying objectives, local constraints which involve both individual agents as well as their neighbors and, crucially, global constraints on the entire system.

Document Details

Document Type
DoD Grant Award
Publication Date
Jan 04, 2017
Source ID
N000141712126

Entities

People

  • Angelia Nedich

Organizations

  • Arizona State University
  • Office of Naval Research
  • United States Navy

Tags

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.