Multi-agent systems arise in several domains of engineering and can be used to solve
problems which are difficult for an individual agent to solve. Strategies for team decision …

This paper introduces a new class of multi-agent discrete-time dynamic games, known in the
literature as dynamic graphical games. For that reason a local performance index is defined …

This monograph provides an exposition of recently developed reinforcement learning-based
techniques for decision and control in human-engineered cognitive systems. The developed …

This paper introduces a model-free reinforcement learning technique that is used to solve a
class of dynamic games known as dynamic graphical games. The graphical game results …

Stackelberg games allow players to access system information differently and take actions
asynchronously. This paper introduces a robust adaptive dynamic programming-based …

Substantial efforts have been undertaken to explore nonzero-sum differential games. Most of
these studies are devoted to devising algorithms to pursue Nash equilibrium, where all …

For the nonzero-sum games, players have taken different strategies to achieve the Nash
equilibrium. However, regarding hierarchical optimization and asymmetric information, Nash …

This paper proposes an online integral reinforcement learning (IRL) algorithm to solve the
Stackelberg games with partially unknown dynamics and input constraints. A general …

This work presents a novel framework based on adaptive learning techniques to solve the
continuous‐time open‐loop Stackelberg games. The method yields real‐time …

Efforts in this paper seek to combine graph theory with adaptive dynamic programming
(ADP) as a reinforcement learning (RL) framework to determine forward-in-time, real-time …