A Distributed, Stochastic Framework for Active Matter

Andréa W. Richa, Dana Randall, Daniel I. Goldman, Sarah Cannon, Joshua J. Daymude, Ram Avinery, Enes Aydin, Bahnisikha Dutta, Shengkai Li, William Savoie, Ross Warkentin, Cem Gökmen, Marta Andrés Arroyo

April 23, 2021 research

We develop a theoretical framework for task-oriented active matter that combines distributed computing, stochastic processes, statistical physics, active matter physics, and robophysics. By harnessing phase changes from statistical physics in our formal modeling and algorithm design, we obtain robust and provable self-organizing behaviors. We then incorporate this theory into swarm robotics platforms, establishing tight analogies between (but not necessarily strict implementations of) the algorithms' rules and our robots' designs. This allows us to critically examine our theoretical algorithms' robustness to the errors and uncertainties of physical environments. Further, we can treat robot swarms as macro-scale active matter systems, studying the inter-robot dynamics as an analogy to particle interactions.

programmable-matter swarm-robotics active-matter markov-chains distributed-algorithms

Joshua J. Daymude

Assistant Professor, SCAI & CBSS

I am a Christian and assistant professor in computer science studying collective emergent behavior and programmable matter through the lens of distributed computing, stochastic processes, and bio-inspired algorithms. I also love gaming and playing music.

Publications

Shengkai Li, Bahnisikha Dutta, Sarah Cannon, Joshua J. Daymude, Ram Avinery, Enes Aydin, Andréa W. Richa, Daniel I. Goldman, Dana Randall (2021). Programming Active Cohesive Granular Matter with Mechanically Induced Phase Changes. Science Advances.

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Joshua J. Daymude (2021). Collaborating in Motion: Distributed and Stochastic Algorithms for Emergent Behavior in Programmable Matter. PhD Dissertation.

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Sarah Cannon, Joshua J. Daymude, Cem Gökmen, Dana Randall, Andréa W. Richa (2019). A Local Stochastic Algorithm for Separation in Heterogeneous Self-Organizing Particle Systems. APPROX/RANDOM 2019.

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Joshua J. Daymude, Kristian Hinnenthal, Andréa W. Richa, Christian Scheideler (2019). Computing by Programmable Particles. Distributed Computing by Mobile Entities.

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Marta Andrés Arroyo, Sarah Cannon, Joshua J. Daymude, Dana Randall, Andréa W. Richa (2018). A Stochastic Approach to Shortcut Bridging in Programmable Matter. Natural Computing.

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William Savoie, Sarah Cannon, Joshua J. Daymude, Ross Warkentin, Shengkai Li, Andréa W. Richa, Dana Randall, Daniel I. Goldman (2018). Phototactic Supersmarticles. Artificial Life and Robotics.

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Sarah Cannon, Joshua J. Daymude, Cem Gökmen, Dana Randall, Andréa W. Richa (2018). Brief Announcement: A Local Stochastic Algorithm for Separation in Heterogeneous Self-Organizing Particle Systems. PODC 2018.

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Marta Andrés Arroyo, Sarah Cannon, Joshua J. Daymude, Dana Randall, Andréa W. Richa (2017). A Stochastic Approach to Shortcut Bridging in Programmable Matter. DNA 2017.

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Sarah Cannon, Joshua J. Daymude, Dana Randall, Andréa W. Richa (2016). A Markov Chain Algorithm for Compression in Self-Organizing Particle Systems. PODC 2016.

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Joshua J. Daymude (2016). Compression in Self-Organizing Particle Systems. Undergraduate Honors Thesis.

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Events

Algorithmic Foundations of Emergent Behavior in Analog Collectives

July 14, 2021 12:15 PM Santa Fe Institute

Collaborating in Motion: Distributed and Stochastic Algorithms for Emergent Behavior in Programmable Matter

March 15, 2021 9:00 AM Arizona State University (Virtual Event)

A Local Stochastic Algorithm for Separation in Heterogeneous Self-Organizing Particle Systems

September 21, 2019 9:00 AM Massachusetts Institute of Technology (MIT)

Stochastic Algorithms for Programmable Matter

April 3, 2019 1:00 PM Arizona State University

Self-Organizing Particle Systems: an Algorithmic Approach to Programmable Matter

November 4, 2018 4:00 PM Campus Innovation Center, Tokyo Tech

A Stochastic Approach to Shortcut Bridging in Programmable Matter

October 6, 2017 1:00 PM Georgia Institute of Technology

Local Stochastic Algorithms for Compression and Shortcut Bridging in Programmable Matter

July 28, 2017 2:05 PM George Washington University

Compression in Self-Organizing Particle Systems

April 6, 2016 11:00 AM Arizona State University