Qin Yang

Qin Yang
University of Georgia | UGA · Department of Computer Science

Doctor of Philosophy
Conduct research and design novel cooperative multi-agent systems, human-robot interaction methods, and AI frameworks.

About

12
Publications
1,105
Reads
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40
Citations
Citations since 2016
12 Research Items
40 Citations
201620172018201920202021202202468101214
201620172018201920202021202202468101214
201620172018201920202021202202468101214
201620172018201920202021202202468101214
Introduction
I am a Ph.D. in Computer Science graduate from the University of Georgia, specializing in Distributed Artificial Intelligence, Swarm Intelligence, Multi-Agent Systems, and Multi-Robot Systems.
Additional affiliations
January 2019 - present
University of Georgia
Position
  • Research Assistant
August 2017 - December 2018
Colorado School of Mines
Position
  • Research Assistant
August 2017 - August 2018
Colorado School of Mines
Position
  • Research Assistant
Education
January 2019 - May 2022
University of Georgia
Field of study
  • Computer Science
August 2017 - December 2018
Colorado School of Mines
Field of study
  • Computer Science
September 2008 - July 2011
Peking University
Field of study
  • Software Engineering

Publications

Publications (12)
Preprint
Full-text available
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 base...
Preprint
Underlying relationships among multiagent systems (MAS) in hazardous scenarios can be represented as game-theoretic models. In adversarial environments, the adversaries can be intentional or unintentional based on their needs and motivations. Agents will adopt suitable decision-making strategies to maximize their current needs and minimize their ex...
Preprint
Full-text available
Cooperation in multi-agent and multi-robot systems can help agents build various formations, shapes, and patterns presenting corresponding functions and purposes adapting to different situations. Relationship between agents such as their spatial proximity and functional similarities could play a crucial role in cooperation between agents. Trust lev...
Preprint
Full-text available
This paper focuses on the teaming aspects and the role of heterogeneity in a multi-robot system applied to robot-aided urban search and rescue (USAR) missions. We specifically propose a needs-driven multi-robot cooperation mechanism represented through a Behavior Tree structure and evaluate the performance of the system in terms of the group utilit...
Preprint
Research in multi-robot and swarm systems has seen significant interest in cooperation and coordination of agents in complex and dynamic environments. To effectively adapt to unknown environments and maximize the utility of the group, robots need to cooperate, share their information, and make a suitable plan according to the specific scenario. Ins...
Preprint
Adversarial Robotics is a burgeoning research area in Swarms and Multi-Agent Systems. It mainly focuses on agents working on dangerous, hazardous, and risky environments, which will prevent robots to achieve their tasks smoothly. In Adversarial Environments, the adversaries can be intentional and unintentional based on their needs and motivation. A...
Preprint
Recently, research in multi-robot and swarm systems has seen significant interest in cooperation and coordination of agents in complex and dynamic environments. To adapt to dynamic environments effectively and maximize the utility of the group, robots need to cooperate, share their information and make a suitable plan according to the specific scen...
Preprint
Multi-Robot System and Swarms are intelligent systems in which a large number of robots are coordinated in a distributed and decentralized way. Each robot may have homogeneous or heterogeneous capabilities and can be programmed with several fundamental control laws adapting to the environment. Through different kinds of relationships built using th...

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Projects

Project (1)
Project
In this project, we focus on building a general Cooperative Heterogeneous self-adaptive and self-upgrade Multi-Agents/Robot System. This framework with corresponding distributed algorithms for communications between robots and negotiation and agreement protocols through a novel priority mechanism following Maslow’s law. It also combines individual decision level, in this part we provide the new network called "GUT" helping agent making decision and dynamically adapte the current situation. In the learning level, it will use various learning methods let individual agent self-upgrade.