Name: Qin Yang
Type: User
Company: Bradley University
Bio: I am an assistant professor specializing in Multi-Agent/Robot Systems, AI, Cognitive Modeling, Robotics, and Human-Robot Interaction.
Twitter: RickYang_2022
Location: 1501 W Bradley Ave, BR 195 | Peoria, IL 61625
Blog: https://www.is3rlab.org/
Qin Yang's Projects
Adopting reasonable strategies is challenging but crucial for an intelligent agent with limited resources working in hazardous, unstructured, and dynamic environments to improve the system utility, decrease the overall cost, and increase mission success probability. Deep Reinforcement Learning (DRL) helps organize agents' behaviors and actions based on their state and represents complex strategies (composition of actions). This research introduces a novel hierarchical strategy decomposition approach based on Bayesian chaining to separate an intricate policy into several simple sub-policies and organize their relationships as Bayesian strategy networks (BSN).
It is a new Game-Theoretic Utility Network called Game-Theoretic Utility Tree (GUT) helping agents making-decision and adapting to adversarial environments, which is also based on the Self-Adaptive Swarm System (SASS).
"Game-theoretic utility tree for multi-robot cooperative pursuit strategy" Paper with Code for 2022 the 54th international symposium on robotics (ISR europe). IEEE. Furthermore, include the codes of Explore Domain implementing in Robotarium.
This is the original code and data for 2020 The IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR). Paper: Needs-driven Heterogeneous Multi-Robot Cooperation in Rescue Missions
Some practice code about OS
Multi-agent systems (MAS) could play a pivotal role in realizing future intelligent workspaces, especially in building so-called artificial social systems, such as self-driving cars and multi-robot systems (MRS). For example, MAS/MRS cooperates to increase mission performance in many applications, including exploration, surveillance, defense, humanitarian, and emergency missions like urban search and rescue.
Qin Yang Personal Website
This version is the original code and data for the 2021 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS. Paper: How Can Robots Trust Each Other For Better Cooperation? A Relative Needs Entropy Based Robot-Robot Trust Assessment Model
This version is the original code and data for the 2020 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS. Paper: Hierarchical Needs Based Self-Adaptive Framework For Cooperative Multi-Robot System
This project is built a general simulation architecture for the Self-Adaptive Swarm System (SASS) with Unity.
Self-Adaptive_Swarm_System(SASS) for 2019 IEEE International Symposium on Multi-Robot and Multi-Agent Systems (MRS) Version. Paper: Self-Reactive Planning of Multi-Robots with Dynamic Task Assignments