Project: Emergence

We utilize tools from statistical physics and Markov chain analysis to investigate how macro-scale behaviors in distributed systems of programmable matter can naturally emerge from local micro-behaviors by individual computational units. When this stochastic approach is combined with the amoebot model from the SOPS project, we translate Markov chains defined at a system level into local, distributed algorithms for self-organizing particle systems that are inherently robust — tolerant of particle faults — and oblivious, using very little memory and communication when compared to the stateful SOPS algorithms.

We can then translate distributed, stochastic algorithms for desirable macroscopic behaviors such as clustering, flocking, exploration, or desegregation into the physical mechanics of simple, analog robots. Ultimately, this project will provide a better end-to-end understanding of how microscopic rules can induce macroscopic behaviors, providing a more systematic approach to building and analyzing swarm robotic systems.


Refereed Journal Papers

Refereed Conference Proceedings

Other Publications

  • Phototactic Supersmarticles. Sarah Cannon, Joshua J. Daymude, William Savoie, Ross Warkentin, Shengkai Li, Daniel I. Goldman, Dana Randall, and Andréa W. Richa. Appeared at the 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics (SWARM ’17). 2017. [Video/Simulation]


Invited Talks

Conference Talks

Poster Presentations

Other Presentations


Current Team

Andréa W. Richa

PI / President’s Professor, Arizona State University[Website]

Dana Randall

PI / Professor, Georgia Institute of Technology[Website]

Daniel I. Goldman

PI / Professor, Georgia Institute of Technology[Website]

Sarah Cannon

Assistant Professor, Claremont McKenna University[Website]

Joshua J. Daymude

Professor, Arizona State University[Website]

Shengkai Li

PhD Student, Georgia Institute of Technology[Website]

Todd Murphey

PI/Professor, Northwestern University


Jamison Weber

PH.D Student, Arizona State University

Ana Pervan

Robotics Engineer, Wayve[website]

Anya Chaturvedi

Factory Automation Engineer, Intel[website]

Joseph Briones

Ph.D Student, Arizona State University[website]

Shunhao Oh

Ph.D Student, Georgia Institute of Technology[website]

Past Members

Bahnisikha Dutta

PhD Student, Georgia Institute of Technology[Website]

William Savoie

PhD, Georgia Institute of Technology 2019 [Website]

Ross Warkentin

Masters of Science, Georgia Institute of Technology 2017[Website]

Cem Gokmen

Undergraduate Researcher, Georgia Institute of Technology 2018[Website]

Marta Andrés Arroyo

Undergraduate Researcher, University of Granada[Website]

Rebecca Martin

Ph.D Student, Carnegie Melon University[website]


  • Collaborative Research: AF: Medium: Markov Chain Algorithms for Problems from Computer Science, Statistical Physics and Self-Organizing Particle Systems. Award #2106917 (ASU), Award #2106687 (Georgia Tech). May. 2021 – Present.
  • Foundations of Emergent Computation and Self-Organized Adaptation. DoD MURI (Multidisciplinary University Research Initiative) Award #W911NF-19-1-0233. Feb. 2019 – Present.
  • Algorithms in the Field: Collaborative Research: A Distributed and Stochastic Algorithmic Framework for Active Matter. NSF CCF (Division of Computing and Communication Foundations): Algorithmic Foundations, Award #1637393 (ASU), Award #1637031 (Georgia Tech). Sept. 2016 – Aug. 2018.
  • Algorithms in the Field: Collaborative Research: Distributed and Stochastic Algorithms for Active Matter: Theory and Practice. NSF CCF (Division of Computing and Communication Foundations): Algorithmic Foundations Award #1733680 (ASU), Award #1733812 (Georgia Tech). Jan. 2018 – Dec. 2020.