YouTube channel: https://www.youtube.com/user/MatthewFricke
Coding for Beginners
CS151: Computer Programming Fundamentals with C++
CS152: Computer Programming Fundamentals with Java
CS201: Discrete Mathematics
CS251: Intermediate Programming with Java
CS261: Mathematical Foundations of Computer Science
CS523: Complex Adaptive Systems (Spring 2013)
CS523: Complex Adaptive Systems (Spring 2017)
CS591: Programming Swarm Robots (Fall 2017)
My work has two main themes: Understanding biological processes through computer simulation and modelling, and the design of search algorithms for teams of robots. The computational biology research focuses on signalling and search processes in the immune system and search strategies in Pogonomyrmex sp . desert seed-harvester ants.
I am technical lead for Swarmathon III and was software lead for Swarmathons I and II. The Swarmathon is a robotics competition held at NASA Kennedy Space Center.
The robotics work is primarily funded by NASA Kennedy Space Center. It is intended to help us understand how autonomous robots on other planets could best search for resources in support of human missions, and also to provide a robotics educational platform for underrepresented students from MUREP institutions. The educational component is in the form of an annual robotics competition called Swarmathon.
Ant Colonies as a Model of Human Computation, Melanie Moses, Tatiana Flanagan, Kenneth Letendre and G. Matthew Fricke, Handbook of Human Computation, Springer, 2014. website
ROCK regulates the intermittent mode of interstitial T cell migration in inflamed lungs. Paulus Mrass, Sreenivasa Oruganti, G. Matthew Fricke, Justyna Tafoya, Janie Byrum , Lihua Yang, Samantha Hamilton, Mark Miller, Melanie Moses and Judy Cannon. Nature Communications (In Press)
Persistence and Adaptation in Immunity: T Cells Balance the Extent and Thoroughness of Search. Fricke, G. Matthew, Kenneth A. Letendre, Melanie E. Moses, and Judy L. Cannon. PLoS Computational Biology 12.3 (2016): e1004818. PDF
Immune-inspired search strategies for robot swarms. G. Matthew Fricke, Joshua Hecker, Judy Cannon, and Melanie Moses. Robotica 34, no. 08 (2016): 1791-1810. Cambridge Press. PDF
Quantifying the Effect of Colony Size and Food Distribution on Harvester Ant Foraging, Tatiana P. Flanagan, Kenneth Letendre, William R. Burnside, G. Matthew Fricke, and Melanie E. Moses, PLoS ONE, 2012.
GetBonNie for building, analyzing, and sharing rule-based models, Bin Hu; G. Matthew Fricke; James R. Faeder; Richard G. Posner; William S. Hlavacek Bioinformatics 2009, Oxford Journals
Receptor aggregation by intermembrane interactions: A Monte Carlo study G. Matthew Fricke; James L. Thomas Biophysical Chemistry Volume 119, Issue 2, 20 Jan 2006; Pages 205-211. PDF
Distinguishing Adaptive Search From Random Search in Robots and T cells, G. M. Fricke, J. P. Hecker, S. R. Black, J. L. Cannon, M. E. Moses, in Proceedings of the Conference on Genetic and Evolutionary Computation, Association for Computing Machinery, 2015.
From Microbiology to Microcontrollers: Robot search patterns inspired by T cell movement, G. Matthew Fricke, Francois Asperti-Boursin, Joshua P. Hecker, Cannon Judy L., and Melanie E. Moses. Proceedings of the 12th European Conference on Artificial Life, The MIT Press, 2013.
How Ants Turn Information into Food, T. Paz Flanagan, K. Letendre, W. Burnside, G. M. Fricke, M. Moses, in IEEE SSCI 2011 - Symposium Series on Computational Intelligence - IEEE Symposium on Artificial Life (2011), pp. 178–185.
Emergent Representation in a Robot Control Architecture, Claiborne, Andy., Fricke, G. Matthew., Lopes, L., Lewis, Joseph., and Luger, George, UNM-NASA PURSUE Conference, (2000).
Swarmathon Rovers with Mounted Grippers
Swarmathon Tutorial Release 0.2.1 (MP4)
PowerSearch3D Videos (MP4)
Pneumatic Gripper TrialsGripper Mockup Video (MP4)
Ant Colony Algorithms (ACOs) are used in shortest-path problem domains such as chip design and network routing. We investigated how three species of the desert harvester ant (Pogonomyrmex Rugosus, Maricopa, and Desertorum) share information about their surroundings, especially with regard to the scaling of information sharing with colony size. This information was compared to computational models of various foraging strategies.
BioNetGen: Biochemical reaction networks are central to understanding and influencing the operation of biological cells. GetBonNie (http://getbonnie.org) and BioNetGen (http://www.bionetgen.org) automate the development of reaction networks so that biologists can create and study detailed models of cellular biochemistry. Poster. Video.You can download the software here: OS X, Windows. Be warned however that these distributions are of RuleBuilder 1.50 Beta bundled with BioNetGen 2.0.28, which are out of date. For the latest builds please go to the bionetgen website.
|T-Cell Targeting Infected Cell||CemPro: Macrophages and T-cells communicate with one another at the cell surface through ligands and receptors. The proteins that form the ligands and receptors cluster during signaling. The mechanism for this clustering is unknown.|
We model proteins on the cell surface with a Metropolis Monte Carlo lattice and measure the conditions under which clustering occurs. We then bring two virtual cell membranes into contact and measure the cross membrane binding forces needed to cause protein phase separation. Paper in Biophysical Chemistry. PowerPoint Web Slideshow. PDF Slideshow.
KomPhy: Algorithms for reconstructing phylogenies from character sequences encounter enormous search spaces even for small numbers of taxa. Techniques are needed to speed up the exploration of these spaces so that larger problems can be approached. In the past neural networks have provided a framework for tackling complex problems very quickly. My thesis describes and tests a new neural network approach to phylogenetic reconstruction called KomPhy. Thesis. Slideshow. Software.
CultureAL: Semester project for David Ackley's Artificial Life course at UNM. CulturAL uses a very simple framework to explore the interaction of learned traits (directly and through peer emulation) and biological traits. Processes such as 'shielding' and the Baldwin Effect are explored. Learning in this model benefits the population as a whole through emulation but is counterproductive for the learner who is much better off copying others and procreating. The population as a whole evolved to minimize direct learning and maximize emulation of peers relying on the background mutation rate to produce enough 'learners' to feed the emulation strategy.. The most prevalent impact shared knowledge has on genetic evolution is shielding, which allows populations to survive that would otherwise die out and allows genetic mutation to explore the fitness landscape with more freedom. Presentation.
Madcat: Extension of the Copycat AI framework to a robotic path finding problem which formed the basis of Joseph Lewis' PhD. Starcat is Joseph's current research. Madcat NASA Student Conference Paper.NASA Autonomous Control Engineering.
BA in Anthropology from Appalachian State University.
BS in Math from the University of New Mexico.
MS in Computer Science from the University of New Mexico.
PhD in Computer Science from the University of New Mexico.
My wife, Suzanne, and I have four boys: Henry, Leo, Owen, and Tristan. We live in Albuquerque, New Mexico, USA. I was born and raised in Shrewsbury, UK, but have lived in Mount Airy, North Carolina and Albuquerque, New Mexico for most of my life. I have been interested in computers since playing with a Commodore 64 when I was ten years old.
Go Figure Software is my contracting company. Through Go Figure Software I have provided programming services to scientists at the UNM Physics Department and Los Alamos National Labs.Europe 2008
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