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相关论文: A Three-Dimensional Pursuit-Evasion Game Based on …

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In practical application, the pursuit-evasion game (PEG) often involves multiple complex and conflicting objectives. The single-objective reinforcement learning (RL) usually focuses on a single optimization objective, and it is difficult to…

系统与控制 · 电气工程与系统科学 2025-03-11 Penglin Hu , Chunhui Zhao , Quan Pan

We study pursuit-evasion differential games between a faster pursuer moving in 3D space and an evader moving in a plane. We first extend the well-known Apollonius circle to 3D space, by which we construct the isochron for the considered two…

系统与控制 · 电气工程与系统科学 2022-03-01 Shuai Li , Chen Wang , Guangming Xie

This paper presents a novel strategy for a multi-agent pursuit-evasion game involving multiple faster pursuers with heterogenous speeds and a single slower evader. We define a geometric region, the evader's safe-reachable set, as the…

多智能体系统 · 计算机科学 2025-11-24 Kamal Mammadov , Damith C. Ranasinghe

Reinforcement Learning (RL)-based motion planning has recently shown the potential to outperform traditional approaches from autonomous navigation to robot manipulation. In this work, we focus on a motion planning task for an evasive target…

机器人学 · 计算机科学 2025-05-12 Zixuan Wu , Sean Ye , Manisha Natarajan , Matthew C. Gombolay

This paper studies a multiplayer reach-avoid differential game in the presence of general polygonal obstacles that block the players' motions. The pursuers cooperate to protect a convex region from the evaders who try to reach the region.…

系统与控制 · 电气工程与系统科学 2024-05-24 Rui Yan , Shuai Mi , Xiaoming Duan , Jintao Chen , Xiangyang Ji

In a pursuit-evasion game, a team of pursuers attempt to capture an evader. The players alternate turns, move with equal speed, and have full information about the state of the game. We consider the most restictive capture condition: a…

度量几何 · 数学 2015-05-05 Andrew Beveridge , Yiqing Cai

Equilibrium learning in adversarial games is an important topic widely examined in the fields of game theory and reinforcement learning (RL). Pursuit-evasion game (PEG), as an important class of real-world games from the fields of robotics…

机器学习 · 计算机科学 2025-12-15 Runyu Lu , Peng Zhang , Ruochuan Shi , Yuanheng Zhu , Dongbin Zhao , Yang Liu , Dong Wang , Cesare Alippi

A reinforcement learning environment with adversary agents is proposed in this work for pursuit-evasion game in the presence of fog of war, which is of both scientific significance and practical importance in aerospace applications. One of…

机器学习 · 计算机科学 2021-08-26 X. Huang

This paper studies a 3D multiplayer reach-avoid differential game with a goal region and a play region. Multiple pursuers defend the goal region by consecutively capturing multiple evaders in the play region. The players have heterogeneous…

最优化与控制 · 数学 2020-02-17 Rui Yan , Xiaoming Duan , Zongying Shi , Yisheng Zhong , Francesco Bullo

This paper considers a pursuit-evasion scenario among three agents -- an evader, a pursuer, and a defender. We design cooperative guidance laws for the evader and the defender team to safeguard the evader from an attacking pursuer. Unlike…

系统与控制 · 电气工程与系统科学 2022-01-19 Abhinav Sinha , Shashi Ranjan Kumar , Dwaipayan Mukherjee

We propose a decentralized solution for a pursuit-evasion game involving a heterogeneous group of rational (selfish) pursuers and a single evader based on the framework of potential games. In the proposed game, the evader aims to delay (or,…

系统与控制 · 电气工程与系统科学 2021-08-19 Yoonjae Lee , Efstathios Bakolas

Pursuit-evasion games are ubiquitous in nature and in an artificial world. In nature, pursuer(s) and evader(s) are intelligent agents that can learn from experience, and dynamics (i.e., Newtonian or Lagrangian) is vital for the pursuer and…

系统与控制 · 电气工程与系统科学 2021-04-06 Hao Xiong , Huanhui Cao , Lin Zhang , Wenjie Lu

This paper investigates obstacle-free simple motion pursuit-evasion problems where the pursuer is faster and game termination is point capture. It is well known that the interior of the Apollonius Circle (AC) is the evader's dominance…

最优化与控制 · 数学 2022-03-24 Michael Dorothy , Dipankar Maity , Daigo Shishika , Alexander Von Moll

Reinforcement learning (RL) often struggles in real-world tasks with high-dimensional state spaces and long horizons, where sparse or fixed rewards severely slow down exploration and cause agents to get trapped in local optima. This paper…

机器人学 · 计算机科学 2026-04-20 Hürkan Şahin , Van Huyen Dang , Erdi Sayar , Alper Yegenoglu , Erdal Kayacan

In this article an $n$-pursuer versus $m$-evader reach-avoid differential game in 3D space is studied. A team of evaders aim to reach a stationary target while avoiding capture by a team of pursuers. The multiplayer scenario is formulated…

最优化与控制 · 数学 2024-02-06 Abinash Agasti , Puduru Viswanadha Reddy , Bharath Bhikkaji

Pursuit-evasion games (PEGs) model interactions between a team of pursuers and an evader in graph-based environments such as urban street networks. Recent advancements have demonstrated the effectiveness of the pre-training and fine-tuning…

人工智能 · 计算机科学 2024-04-22 Pengdeng Li , Shuxin Li , Xinrun Wang , Jakub Cerny , Youzhi Zhang , Stephen McAleer , Hau Chan , Bo An

Dropped into an unknown environment, what should an agent do to quickly learn about the environment and how to accomplish diverse tasks within it? We address this question within the goal-conditioned reinforcement learning paradigm, by…

机器学习 · 计算机科学 2023-03-24 Edward S. Hu , Richard Chang , Oleh Rybkin , Dinesh Jayaraman

In this paper, we address pursuit-evasion problems involving multiple pursuers and multiple evaders. The pursuer and the evader teams are assumed to be heterogeneous, in the sense that each team has agents with different speed capabilities.…

最优化与控制 · 数学 2020-06-22 Venkata Ramana Makkapati , Panagiotis Tsiotras

In classical works on a planar differential pursuit-evasion game with a faster pursuer, the intercept point resulting from the equilibrium strategies lies on the Apollonius circle. This property was exploited for the construction of the…

Fictitious play (FP) is a well-studied algorithm that enables agents to learn Nash equilibrium in games with certain reward structures. However, when agents have no prior knowledge of the reward functions, FP faces a major challenge: the…

计算机科学与博弈论 · 计算机科学 2025-08-28 Semih Kara , Tamer Başar
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