Multi-Agent-Welcome
Exploring Collaboration & Innovation in Multi-Agent Systems
Our Multi-Agent Group focuses on cutting-edge research in robotics, reinforcement learning, and multi-agent systems. We aim to advance the understanding and practical application of collaborative AI systems for solving complex, real-world problems.
![2108.10470] Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning](https://ar5iv.labs.arxiv.org/html/2108.10470/assets/x17.png)
Meet Our Team
Our team is dedicated to advancing research in robotics, artificial intelligence, and multi-agent systems. We are a passionate group of researchers, students, and collaborators working together to solve complex challenges through innovation, collaboration, and cutting-edge technology.
Professor Maria Gini
Principal Investigator
Specializes in Reinforcement Learning and Multi-Agent Systems
Sarah Boelter (she/her)
3rd Year PhD Candidate in Computer Science
Education: B.S. in Computer Science from University of Alaska Anchorage, M.S. in Computer Science from University of Minnesota
Experience: Software Engineer at Lockheed Martin RMS
Research Interests: Symbiotic Autonomy, Robotics in Extreme Environments, Autonomous Decision Making, Multi-Agent Systems
Fun Fact: I have a cat named Squeak and I like biking
Mario Jerez (they/them)
1st Year PhD Student in Computer Science
Education: Bachelor’s of Arts at Sarah Lawrence College
Experience: Software Consultant and Full Stack Product Developer for ABACUS Software at Avolution, Implementation Consultant at FAST Enterprises, Graduate Teaching Assistant at UMN
Research Interests: Multi-Agent Systems and Machine Learning
Fun Fact: Rock climbing, frolicking in nature
Franklin Xavier (he/him)
2nd Year Master’s in Robotics
Education: B.E. Mechanical Engineering at Anna University
Experience: Research Assistant at UMN Networking Research Group and Agricultural Robotics Lab, Design Engineer at Thermax Limited and Armstrong International
Research Interests: Deep Learning, Computer Vision, and Natural Language Processing
Jamie McArton (he/him)
3rd Year Undergraduate (B.S. in Computer Science)
Research Interests: Cybersecurity, AI (especially in human interaction), and Robotics
Fun Fact: I play Splatoon 3 competitively and like to draw digitally as a hobbyist!
Multi-Agent-About-Us
Multi-Agent Reinforcement Learning (MARL)
We focus on developing and implementing advanced MARL algorithms to enhance collaboration and decision-making in environments with multiple intelligent agents.
Multi-Agent Systems (MAS)
Our research delves into the design and analysis of multi-agent systems, exploring their applications in robotics, distributed control, and complex system optimization.
Federated Learning and Robotics
By combining federated learning with robotics, we aim to address challenges in decentralized data privacy and adaptive learning in real-world multi-agent environments.
Explore Our Ongoing Projects
Our team is working on innovative projects in Multi-Agent Reinforcement Learning, Robotics, and Federated Learning. Here's a glimpse of some of our key initiatives.
Federated Learning for Traffic Flow Prediction
Using Transformer-based models to enable distributed learning for accurate traffic flow forecasting while ensuring data privacy.
Multi-Agent Path Planning
Developing time-extended graph approaches and auction mechanisms to enable efficient and collision-free multi-agent pathfinding.
Reinforcement Learning for Cooperative Robotics
Designing collaborative strategies for robots to work together in complex environments, leveraging PPO and MAPPO algorithms.
Optimization in Multi-Agent Systems
Investigating optimization strategies for resource allocation, task distribution, and decision-making in distributed systems.
Autonomous Drone Swarms
Exploring the use of autonomous drones in cooperative missions, including disaster response and environmental monitoring.
Robotics for Lunar Exploration
Developing systems for exploring and assessing lunar caves and pits for long-term human habitation as part of NASA's Artemis mission.
Join us in advancing robotics and multi-agent systems!