This book presents an overview of formal decision making methods for decentralized
cooperative systems. It is aimed at graduate students and researchers in the fields of …

Our goal in writing this book has been to provide a comprehensive, mathematically rigorous,
but still accessible treatment of the interaction between information and control in multi …

We propose a theoretical framework for approximate planning and learning in partially
observed systems. Our framework is based on the fundamental notion of information state …

A general model of decentralized stochastic control called partial history sharing information
structure is presented. In this model, at each step the controllers share part of their …

In many areas of applied mathematics, decentralization of information is a ubiquitous
attribute affecting how to approach a stochastic optimization, decision and estimation, or …

This tutorial paper provides a comprehensive characterization of information structures in
team decision problems and their impact on the tractability of team optimization. Solution …

In this paper, a centralized control model for optimal management and operation of a smart
network of microgrids (SNMs) is designed. The proposed control strategy considers grid …

We extend trust region policy optimization (TRPO) to cooperative multiagent reinforcement
learning (MARL) for partially observable Markov games (POMGs). We show that the policy …

We study provable multi-agent reinforcement learning (MARL) in the general framework of
partially observable stochastic games (POSGs). To circumvent the known hardness results …

A model of stochastic games where multiple controllers jointly control the evolution of the
state of a dynamic system but have access to different information about the state and action …