Maryland Robotics Student Seminar: Latent Representations and Intrinsic Laws of Complex Systems

Friday, October 29, 2021
2:00 p.m.
CSIC-1115
Lena Johnson
301 405 8870
ljohns14@umd.edu

Learning Latent Representations and Intrinsic Laws of Complex Systems

Christos N. Mavridis
PhD Candidate, Electrical and Computer Engineering
Advisor: Dr. John Baras

Abstract

The phenomenal increase of interest towards intelligent autonomous systems observed in recent years is leading the way towards automation augmented with actual machine intelligence. How can a robot reliably react to and operate within its environment? How is this connected to how humans dynamically process sensory information? The answer to these famous problems are not only linked to deeper understanding, but also to the decision-making potential of autonomous systems in general. Towards this direction, it is important to understand and formally analyze the fundamental properties of learning, as a continuous, dynamic, and adaptive process of acquiring new understanding, knowledge, or skills. 
 
This work deals with two broad and open learning and control problems with applications in image and sound classification, graph partitioning, reinforcement learning, identification and control of multi-agent systems, intelligent transportation, and human-robot interaction. The first problem is connected to the existence of a universal learning architecture in human cognition, which is a widely accepted conjecture supported by established experimental findings from neuroscience. The second problem is about learning the intrinsic laws of complex networked systems, ranging from animal flocks to social networks. This is a time-dependent learning problem with dynamical constraints, where data are often noisy and sparse.

This is one of the very first endeavors to develop a progressive learning approach in the context of decision-making in such a diverse research area. The insights provided by this work can lead to new developments in machine intelligence based on autonomous, continuously adaptive algorithms that can be used reliably in real-life applications to serve the common good.

 

About the Robotics Student Seminars
The Robotics Student Seminars at the University of Maryland College Park are a student-run series of talks given by current robotics students.

The purpose of these talks is to:

  • Encourage interaction between Robotics students from different subfields;
  • Provide an opportunity for Robotics students to be aware of and possibly get involved in the research their peers are conducting;
  • Provide an opportunity for Robotics students to receive feedback on their current research;
  • Provide speaking opportunities for Robotics students.

remind we with google calendar

 

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