Research Presentation
Bayesian Soft Actor-Critic: A Directed Acyclic Strategy Graph Based Deep Reinforcement Learning
A strategy describes the general plan of an agent achieving short-term or long-term goals under uncertainty, which involves setting sub-goals and priorities, determining action se- quences to fulfill the tasks, and mobilizing resources to execute the actions. [TIST Paper | 01/24/2024]
Innate-Values-driven Reinforcement Learning for Cooperative Multi-Agent Systems
Innate values describe agents’ intrinsic motivations, which reflect their inherent interests and preferences to pursue goals and drive them to develop diverse skills satisfying their various needs. [arXv Paper | 01/10/2024]
Edge Computing based Human-Robot Cognitive Fusion: A Medical Case Study in the Autism Spectrum Disorder Therapy
People with ASD usually have problems with social communication, regular interaction, and restricted or repetitive behaviors or interests. Robot-assisted therapy (RAT) is an emerging field that has attracted many researchers to study and benefited children with ASD. [arXv Paper | 01/01/2024]
A Hierarchical Game-Theoretic Decision-Making for Cooperative Multiagent Systems Under the Presence of Adversarial Agents
This research proposes a new network model called the Game-Theoretic Utility Tree (GUT), combining the core principles of game theory and utility theory to achieve cooperative decision-making for MAS in adversarial environments. [SAC Paper | 03/28/2023]
Talks
Hierarchical Needs-driven Self-adaptive Multi-Agent Systems: From Individual Utilities to Swarm Intelligence
I was invited by the Cognitive Robotics and AI Lab (CRAI) in the College of Aeronautics and Engineering at Kent State University to give a talk about my current research on AI and Robotics. [Invited Talk | 06/06/2023]
News
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Received the Faculty Scholarship Award 2024
Dr. Yang received the Faculty Scholarship Award (FSA) 2024 at Bradley University, which funded him with $6,000 to develop a new reinforcement learning (RL) model based on the Bayesian Strategy Network (BSN) for robot locomotion and planning.
For more details, please check.
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Paper Accepted by the Top AI Journal "ACM Transactions on Intelligent Systems and Technology"
Our paper "Bayesian Strategy Networks Based Soft Actor-Critic Learning" has been accepted by the top AI journal "ACM Transactions on Intelligent Systems and Technology (TIST)".
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Paper Accepted as a poster paper by the 39th ACM/SIGAPP Symposium On Applied Computing (SAC) 2024
Our paper "Bayesian Soft Actor-Critic: A Directed Acyclic Strategy Graph Based Deep Reinforcement Learning" has been accepted as a poster paper by the SAC 2024 on Intelligent Robotics and Multi-Agent Systems (IRMAS) track.
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Organizing AAAI24 Workshop: "Cooperative Multi-Agent Systems Decision-Making and Learning: From Individual Needs to Swarm Intelligence"
Our proposal "Cooperative Multi-Agent Systems Decision-Making and Learning: From Individual Needs to Swarm Intelligence" has been accepted by the 38th AAAI Conference Workshop Program.
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Receive the Caterpillar Fellowship $ 5K
Dr. Yang's proposal has been accepted by the Caterpillar Fellowship for funding in the amount of $ 5,000. This project will focus on 5G Connected Cooperative Multi-Agent Systems Localization and Navigation research and education.
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Paper Accepted by the 38th ACM/SIGAPP Symposium On Applied Computing (SAC) 2023
Our paper "A Hierarchical Game-Theoretic Decision-Making for Cooperative Multiagent Systems Under the Presence of Adversarial Agents" has been accepted by the SAC 2023 on Intelligent Robotics and Multi-Agent Systems (IRMAS) track.
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Paper Accepted by the AAAI 2023 Bridge Program
Our paper "Hierarchical Needs-driven Agent Learning Systems: From Deep Reinforcement Learning To Diverse Strategies" has been accepted by the 37th AAAI Conference on Artificial Intelligence and Robotics Bridge Program.
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Paper Accepted by the ANT 2023
Our paper "A Strategy-Oriented Bayesian Soft Actor-Critic Model" has been accepted by the Elsevier Science 14th International Conference on Ambient Systems, Networks and Technologies (ANT 2023).