BIC: EMT: Reimagining Evolutionary Computation

Michigan State University, East Lansing MI

Investigators

Abstract

Evolution has a remarkable ability to design organisms possessing novel features that enable them to survive, and even thrive, in challenging environments. To a human observer, the biochemical and physiological complexity of living organisms is amazing, leading some to disbelieve that such biological designs could have been accomplished by evolution alone. Considering the levels of biocomplexity found throughout nature - the development of an embryo from a single-cell; the delicate balance of an ecosystem in a rainforest; all the way to the reasoning power of the human brain, complex and elegant adaptive designs abound. As we slowly understand more details about how evolution produces such complex traits, it becomes clear that this is a powerful constructive force that we need to fully understand in order to harness its potential in solving difficult computational design problems. The twin goals of this project are to learn more about the mechanisms by which evolution produces innovative complex features, and then to apply this newfound understanding to develop a new generation of evolution-based algorithms for solving computational problems. In the process, we will use a mathematical framework for the study of complexity in biological systems to better understand the natural design process. We will start this work by answering fundamental questions in evolutionary biology and ecology including: Why do complex designs arise faster in multi-species ecosystems? If organisms have the capacity to modify their environment and communicate with one another, will this spur open-ended complexity growth? and How can we harness these forces to solve design problems? The evolving system that we use in this study is an artificial one, based on self-replicating computer programs, that nonetheless exhibit the key characteristics of natural evolving systems - most notably the ability to produce novel complex traits and innovative solutions to problems. These "digital organisms" exist in a user-defined computational environment, and their genomes are composed can theoretically perform any computable mathematical function. Indeed, we have witnessed a wide variety of unexpected and innovative adaptations arise through evolution in Avida. This system allows us to explore fundamental questions in evolutionary biology with speed, detail and precision that would not be possible in any natural system. Ideally it is a tool that will allow us to fully understand the origins of biocomplexity, and constructively make use of these same forces that were able to produce human intelligence in the natural world.