Publications de Joshua Evan Auerbach

Inquiry-Based Learning with RoboGen: An Open-Source Software and Hardware Platform for Robotics and Artificial Intelligence

Dario Floreano, Joshua Evan Auerbach, Przemyslaw Mariusz Kornatowski, Alice Ghislaine Concordel

It has often been found that students appreciate hands-on work, and find that they learn more with courses that include a project than those relying solely on conventional lectures and tests. This type of project driven learning is a key component of “Inqu ...

2019

The Seamless Peer and Cloud Evolution Framework

Dario Floreano, Joshua Evan Auerbach, Giovanni Iacca, Guillaume Paul Olivier Leclerc

Evolutionary algorithms are increasingly being applied to problems that are too computationally expensive to run on a single personal computer due to costly fitness function evaluations and/or large numbers of fitness evaluations. Here, we introduce the Se ...

ACM Press2016

Rapid Evolution of Robot Gaits

Dario Floreano, Joshua Evan Auerbach, Przemyslaw Mariusz Kornatowski, Grégoire Hilaire Marie Heitz

The promise of Evolutionary Robotics (ER) to completely automatize the design of robot controllers and/or morphologies is an idea with great appeal not only to researchers, but also to students. However, when attempting to grab and hold student interest, t ...

ACM2015

RoboGen: Robot Generation through Artificial Evolution

Dario Floreano, Ilya Loshchilov, Joshua Evan Auerbach, Andrea Maesani, Ludovic Daler, Przemyslaw Mariusz Kornatowski, Titus Cieslewski, Grégoire Hilaire Marie Heitz, Deniz Aydin, Pradeep Ruben Fernando

Science instructors from a wide range of disciplines agree that hands-on laboratory components of courses are pedagogically necessary (Freedman, 1997). However, certain shortcomings of current laboratory exercises have been pointed out by several authors ( ...

The MIT Press2014

Programmable Self-assembly with Chained Soft Cells: An Algorithm to Fold into 2-D Shapes

Dario Floreano, Joshua Evan Auerbach, Jürg Markus Germann

Programmable self-assembly of chained modules holds potential for the automatic shape formation of morphologically adapted robots. However, current systems are limited to modules of uniform rigidity, which restricts the range of obtainable morphologies and ...

Springer International Publishing2014

Online Extreme Evolutionary Learning Machines

Dario Floreano, Joshua Evan Auerbach

Recently, the notion that the brain is fundamentally a prediction machine has gained traction within the cognitive science community. Consequently, the ability to learn accurate predictors from experience is crucial to creating intelligent robots. However, ...

The MIT Press2014

Flexible Task Graphs:Unified Restricted Thread Programming Model for Java

Rachid Guerraoui, Jesper Honig Spring, Joshua Evan Auerbach

2008