Multi-Agent Decision Making

Multi-Robot Task Allocation Games in Dynamically Changing Environments with Application to Trash Collection

Shinkyu Park, Assistant Professor, Electrical and Computer Engineering, KAUST

Apr 1, 11:45 - 12:30

KAUST

Featured Sessions

RobotoKAUST Multi-Robot Learning/Coordination Multi-Agent Decision Making game theory

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Principles and Algorithms for Multi-Agent Decision Making

Shinkyu Park, Assistant Professor, Electrical and Computer Engineering

Nov 20, 12:00 - 13:00

B9 L2 R2322 H1

Multi-Agent Decision Making

A multi-agent system consists of individual agents sharing information and coordinating for collective decision making. The study of multi-agent decision making has important implications in conceiving networked engineering systems - a team of mobile robots or a fleet of drones - that can effectively coordinate to carry out assigned missions. Modeling such system as feedback interconnections of many smaller units allows us to examine its long-term behavior using analytical tools from feedback control theory, such as Lyapunov stability and bifurcation analysis. In this presentation, we discuss how such tools can be used to predict asymptotic behavior of the agents' decision making process and also to design computational models of the decision making process.

Lucas Câmara Dantas Bezerra

Ph.D. Student, Electrical and Computer Engineering

Multi-Agent Decision Making Deep learning Multi-agent systems Robotics and Control

PhD candidate working on cooperation in multi-agent systems through Multi-Agent Reinforcement Learning (MARL). He is affiliated with the Distributed Systems and Autonomy (DSA) group, under supervision of Professor Shinkyu Park.