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 • 12 May 2024 • Matthew Andres Moreno, Santiago Rodriguez-Papa, Emily Dolson
Here, we set out to assess (1) if spatial structure, ecology, and selection pressure leave detectable signatures in phylogenetic structure, (2) the extent, in particular, to which ecology can be detected and discerned in the presence of spatial structure, and (3) the extent to which these phylogenetic signatures generalize across evolutionary systems.
no code implementations • 6 May 2024 • Matthew Andres Moreno, Connor Yang, Emily Dolson, Luis Zaman
Emerging ML/AI hardware accelerators, like the 850, 000 processor Cerebras Wafer-Scale Engine (WSE), hold great promise to scale up the capabilities of evolutionary computation.
no code implementations • 16 Apr 2024 • Matthew Andres Moreno, Connor Yang, Emily Dolson, Luis Zaman
Continuing improvements in computing hardware are poised to transform capabilities for in silico modeling of cross-scale phenomena underlying major open questions in evolutionary biology and artificial life, such as transitions in individuality, eco-evolutionary dynamics, and rare evolutionary events.
no code implementations • 16 Apr 2024 • Matthew Andres Moreno
Complexity is a signature quality of interest in artificial life systems.
no code implementations • 2 Feb 2024 • Alexander Lalejini, Marcos Sanson, Jack Garbus, Matthew Andres Moreno, Emily Dolson
We introduce phylogeny-informed subsampling, a new class of subsampling methods that exploit runtime phylogenetic analyses for solving test-based problems.
no code implementations • 6 Jun 2023 • Alexander Lalejini, Matthew Andres Moreno, Jose Guadalupe Hernandez, Emily Dolson
Thus far, phylogenetic analyses have primarily been applied as post-hoc analyses used to deepen our understanding of existing evolutionary algorithms.
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.
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.