Category: Research

Learning an Evolvable Genotype-Phenotype Mapping

By Matthew Andres Moreno on June 8, 2018 in Research / 0 Comments
Learning an Evolvable Genotype-Phenotype Mapping

This material is cross-posted from my personal blog. You can find the original version here. This paper provides profound insights for GA design, in specific the automatic generation of evolvable genotype-phenotype mappings using ANN autoencoders. It is clearly elucidated, with a firm grasp of the foundational literature in both biological evolution and evolutionary computation. The results are promising and establish a rich line of inquiry for researchers to pursue. — Reviewer #1 Thanks, Reviewer #1. My co-authors (Charles Ofria and Wolfgang Banzhaf) and I are really excited about Learning an Evolvable Genotype-Phenotype Mapping, too! (Almost as excited as we are about traveling to Kyoto this summer to present it at the 2018 GECCO conference.) I hope this blog post will get you on board, too, or at least prompt some good chin-scratching (the academic equivalent of […]

Signal GP, an Introduction

Signal GP, an Introduction

Genetic programming (GP) is the application of natural principles to evolve computer programs rather than writing them by hand. Here, I introduce Signal GP, a new type of linear GP representation designed to more directly capture the event-driven programming paradigm, allowing evolved programs to handle signals from the environment or from other agents in a more biologically inspired way than traditional linear GP representations. GP is successful across a growing set of problem domains. Signal GP targets problems where programs, much like biological organisms, must react on-the-fly to signals in the environment or from other agents. I’ll address the following questions in this blog post: What is linear genetic programming? What exactly is the event-driven programming paradigm, why is it so powerful, and why do we want to capture it in GP? And, how exactly does […]

Introductory Glimpses of Evolvability for Computer Scientists

By Matthew Andres Moreno on October 27, 2017 in Research, Review / 0 Comments
Introductory Glimpses of Evolvability for Computer Scientists

This is one of a series of posts on evolvability. It is based off my undergraduate thesis, which I wrote at the University of Puget Sound under advisors Dr. America Chambers and Dr. Adam Smith. The original thesis is available here. Introductory Glimpses of Evolvability for Computer Scientists How can the structure of an evolving organism affect the phenotypic outcomes of mutational perturbation? We will walk through a thought example that casts this question in a light more familiar to programmers. Computer scientists who have worked on software understand that two pieces of code that meet identical specifications — return identical output for any input given — can differ vastly in difficulty to extend, modify, or maintain. Software implementation, internal structures largely invisible from the perspective of an external interface, accounts for this discrepancy. Computer scientists […]

Introductory Glimpses of Evolvability for Biologists

By Matthew Andres Moreno on October 20, 2017 in Research, Review / 0 Comments
Introductory Glimpses of Evolvability for Biologists

This is one of a series of posts on evolvability. It is based off my undergraduate thesis, which I wrote at the University of Puget Sound under advisors Dr. America Chambers and Dr. Adam Smith. The original thesis is available here. Introductory Glimpses of Evolvability for Biologists The idea that phenotypic outcomes of mutation are non-arbitrary can be unfamiliar, or even uncomfortable, to biologists [Kirschner and Gerhart, 2005, p 219]. It is consensus among evolutionary biologists that genetic mutation is random. The alternative — the theory of adaptive mutation — is controversial and widely discredited [Sniegowski and Lenski, 1995]. It is therefore essential to note that discussions of evolvability are not predicated on adaptive mutation. The key difference is that adaptive mutation hypothesizes that genetic mutation is non-arbitrary while discussions of evolvability center on the idea […]

Defining Evolvability

By Matthew Andres Moreno on October 13, 2017 in Research, Review / 0 Comments
Defining Evolvability

This is one of a series of posts on evolvability. It is based off my undergraduate thesis, which I wrote at the University of Puget Sound under advisors Dr. America Chambers and Dr. Adam Smith. The original thesis is available here. Defining Evolvability Figure 1 Some of my favorite biological phenotypes… biased towards cooperative photographic subjects! While biological phenotypic adaptation is indeed spectacular, another marvel of biology lurks just below our appreciation for phenotypes well-suited to their respective environments. It is hypothesized that biological organisms exhibit adaptation to the evolutionary process itself, not just to their environment over the course of their lifespans. That is, biological organisms are thought to possess traits that facilitate the evolutionary process. The term evolvability was coined to describe such traits. A general consensus exists in the literature that evolvability stems […]