IMAP-QL: an improved multi-agent pursuit path-planning based on Q-learning
Multi-agent path planning is a complex problem aiming to find the shortest trajectory. In this
paper, we propose a cooperative path planning based on a hybridisation of two motion …
paper, we propose a cooperative path planning based on a hybridisation of two motion …
Multi-Agent Dynamic Leader-Follower Path Planning Applied to the Multi-Pursuer Multi-Evader Game
Multi-agent collaborative path planning focuses on how the agents have to coordinate their
displacements in the environment to achieve different targets or to cover a specific zone in a …
displacements in the environment to achieve different targets or to cover a specific zone in a …
Multi-agent Ludo Game Collaborative Path Planning based on Markov Decision Process
The multi-agent path planning problem is usually addressed via the use of reinforcement
learning methods. In this article, a new Lludo game path planning algorithm based on Q …
learning methods. In this article, a new Lludo game path planning algorithm based on Q …
Mobile agents path planning based on an extension of Bug-Algorithms and applied to the pursuit-evasion game
MEH Souidi, S Piao, G Li - Web Intelligence, 2017 - content.iospress.com
Pursuit-evasion game is a known problem in Multi-agent systems. This problem is
approached through the elaboration of different task coordination and path planning …
approached through the elaboration of different task coordination and path planning …
Multi-agent path planning approach using assignment strategy variations in pursuit of moving targets
This study aims to investigate the problem of assignment strategies for multiple agents. In
multi-agent scenarios, agents compute a path towards the goal, while these goal …
multi-agent scenarios, agents compute a path towards the goal, while these goal …
Comparative study of reinforcement learning methods in path planning
D Obawole - 2021 - scholar.uwindsor.ca
In order to perform a large variety of tasks and achieve human-level performance in complex
real-world environments, an intelligent agent must be able to learn from its dynamically …
real-world environments, an intelligent agent must be able to learn from its dynamically …
Q-learning Based System for Path Planning with UAV Swarms in Obstacle Environments
Path Planning methods for autonomous control of Unmanned Aerial Vehicle (UAV) swarms
are on the rise because of all the advantages they bring. There are more and more …
are on the rise because of all the advantages they bring. There are more and more …
Curriculum-Based Reinforcement Learning for an Effective Multi-Agent Path Planning Algorithm in Warehouse Scenarios
IRL De Oliveira, KB De Carvalho… - 2023 15th IEEE …, 2023 - ieeexplore.ieee.org
Multi-robot systems can provide substantial increase in efficiency and/or flexibility in different
scenarios. Applications in various settings have been studied in the literature, such as …
scenarios. Applications in various settings have been studied in the literature, such as …
A strategic search algorithm in multi-agent and multiple target environment
The aim of this study is to investigate how to solve the path-planning problem of multiple
competing players towards moving targets within a dynamically changing environment. A …
competing players towards moving targets within a dynamically changing environment. A …
A reinforcement learning based multiple strategy framework for tracking a moving target
The pursuit-evasion game has been a classic research topic in the field of mobile robotics.
Reinforcement learning (RL), which shows outstanding advantages in the decision-making …
Reinforcement learning (RL), which shows outstanding advantages in the decision-making …