no code implementations • 12 May 2024 • Matthew Andres Moreno, Santiago Rodriguez Papa, Charles Ofria
In this work, we track the co-evolution of novelty, complexity, and adaptation in a case study from the DISHTINY simulation system, which is designed to study the evolution of digital multicellularity.
no code implementations • 4 Jan 2023 • Ryan Boldi, Martin Briesch, Dominik Sobania, Alexander Lalejini, Thomas Helmuth, Franz Rothlauf, Charles Ofria, Lee Spector
Random down-sampled lexicase selection evaluates individuals on only a random subset of the training cases allowing for more individuals to be explored with the same amount of program executions.
2 code implementations • 29 Apr 2022 • Jose Guadalupe Hernandez, Alexander Lalejini, Charles Ofria
We consider exploitation both with and without constraints, and we divide exploration into two aspects: diversity exploration (the ability to simultaneously explore multiple pathways) and valley-crossing exploration (the ability to cross wider and wider fitness valleys).
1 code implementation • 10 Aug 2021 • Matthew Andres Moreno, Alexander Lalejini, Charles Ofria
Genetic programming and artificial life systems commonly employ tag-matching schemes to determine interactions between model components.
no code implementations • 1 Aug 2021 • Matthew Andres Moreno, Santiago Rodriguez Papa, Alexander Lalejini, Charles Ofria
Event-driven genetic programming representations have been shown to outperform traditional imperative representations on interaction-intensive problems.
1 code implementation • 20 Jul 2021 • Jose Guadalupe Hernandez, Alexander Lalejini, Charles Ofria
We use our exploration diagnostic to investigate the exploratory capacity of lexicase selection and several of its variants: epsilon lexicase, down-sampled lexicase, cohort lexicase, and novelty-lexicase.
no code implementations • 20 Apr 2021 • Matthew Andres Moreno, Charles Ofria
These digital cells were allowed to form and replicate kin groups by selectively adjoining or expelling daughter cells.
1 code implementation • 16 Dec 2020 • Alexander Lalejini, Matthew Andres Moreno, Charles Ofria
We demonstrate the functionality of tag-based regulation on a range of program synthesis problems.
1 code implementation • 15 Apr 2018 • Alexander Lalejini, Charles Ofria
We present SignalGP, a new genetic programming (GP) technique designed to incorporate the event-driven programming paradigm into computational evolution's toolbox.
no code implementations • 9 Mar 2018 • Joel Lehman, Jeff Clune, Dusan Misevic, Christoph Adami, Lee Altenberg, Julie Beaulieu, Peter J. Bentley, Samuel Bernard, Guillaume Beslon, David M. Bryson, Patryk Chrabaszcz, Nick Cheney, Antoine Cully, Stephane Doncieux, Fred C. Dyer, Kai Olav Ellefsen, Robert Feldt, Stephan Fischer, Stephanie Forrest, Antoine Frénoy, Christian Gagné, Leni Le Goff, Laura M. Grabowski, Babak Hodjat, Frank Hutter, Laurent Keller, Carole Knibbe, Peter Krcah, Richard E. Lenski, Hod Lipson, Robert MacCurdy, Carlos Maestre, Risto Miikkulainen, Sara Mitri, David E. Moriarty, Jean-Baptiste Mouret, Anh Nguyen, Charles Ofria, Marc Parizeau, David Parsons, Robert T. Pennock, William F. Punch, Thomas S. Ray, Marc Schoenauer, Eric Shulte, Karl Sims, Kenneth O. Stanley, François Taddei, Danesh Tarapore, Simon Thibault, Westley Weimer, Richard Watson, Jason Yosinski
Biological evolution provides a creative fount of complex and subtle adaptations, often surprising the scientists who discover them.
no code implementations • 3 Sep 2013 • David M. Bryson, Charles Ofria
We evaluated six different types of architectural features for the virtual CPUs: (1) genetic flexibility: we allowed digital organisms to more precisely modify the function of genetic instructions, (2) memory: we provided an increased number of registers in the virtual CPUs, (3) decoupled sensors and actuators: we separated input and output operations to enable greater control over data flow.