Iterated reasoning with mutual information in cooperative and byzantine decentralized teaming
Information sharing is key in building team cognition and enables coordination and
cooperation. High-performing human teams also benefit from acting strategically with …
cooperation. High-performing human teams also benefit from acting strategically with …
Toward multi-target self-organizing pursuit in a partially observable Markov game
The multiple-target self-organizing pursuit (SOP) problem has wide applications and has
been considered a challenging self-organization game for distributed systems, in which …
been considered a challenging self-organization game for distributed systems, in which …
Parallel multi-speed pursuit-evasion game algorithms
Abstract Pursuit-Evasion Game (PEG) consists of a team of pursuers trying to capture one or
more evaders. PEG is important due to its application in surveillance, search and rescue …
more evaders. PEG is important due to its application in surveillance, search and rescue …
[HTML][HTML] A pursuit-evasion game robot controller design based on a neural network with an improved optimization algorithm
MW Hasan, LG Ibrahim - Results in Control and Optimization, 2024 - Elsevier
A pursuit-evasion game (PEG) is a type of game that utilizes one or several cooperative
pursuers to capture one or several evaders. The PEG game concept has been used in …
pursuers to capture one or several evaders. The PEG game concept has been used in …
Adaptive Decision-Making in Attack-Defense Games With Bayesian Inference of Rationality Level
H Fang, P Yi - IEEE Transactions on Industrial Electronics, 2024 - ieeexplore.ieee.org
This article investigates two-player attack-defense (AD) games involving players with
bounded rationality, where the defender aims to intercept the attacker, while the attacker …
bounded rationality, where the defender aims to intercept the attacker, while the attacker …
Learning Nash equilibria in zero-sum stochastic games via entropy-regularized policy approximation
Y Guan, Q Zhang, P Tsiotras - arXiv preprint arXiv:2009.00162, 2020 - arxiv.org
We explore the use of policy approximations to reduce the computational cost of learning
Nash equilibria in zero-sum stochastic games. We propose a new Q-learning type algorithm …
Nash equilibria in zero-sum stochastic games. We propose a new Q-learning type algorithm …
Hierarchical multi-robot pursuit with deep reinforcement learning and navigation planning
W Chen, Y Zhu - … 39th Youth Academic Annual Conference of …, 2024 - ieeexplore.ieee.org
Robotic systems have been used to solve multiple important problems, including pursuit.
However, traditional methods in game theory and controlling make it difficult to resolve …
However, traditional methods in game theory and controlling make it difficult to resolve …
Hierarchical decompositions of stochastic pursuit-evasion games
In this work we present a hierarchical framework for solving discrete stochastic pursuit-
evasion games (PEGs) in large grid worlds. Given a partition of the grid world into …
evasion games (PEGs) in large grid worlds. Given a partition of the grid world into …
Model Predictive Control based Target Defense with Attacker Trajectory Prediction
This paper considers a target attack defense scenario where the attacker aims to reach the
target while avoiding the defender, and the defender wants to protect the target by …
target while avoiding the defender, and the defender wants to protect the target by …
Enhancing Teamwork in Multi-Robot Systems: Embodied Intelligence via Model-and Data-Driven Approaches
E Seraj - 2023 - hal.science
High-performing human teams leverage intelligent and efficient communication and coordi-
nation strategies to collaboratively maximize their joint utility. Inspired by teaming behaviors …
nation strategies to collaboratively maximize their joint utility. Inspired by teaming behaviors …