Digital Organism

A digital organism is a self-replicating computer program that mutates and evolves. Digital organisms are used as a tool to study the dynamics of Darwinian evolution, and to test or verify specific hypotheses or mathematical models of evolution.

History

Digital organisms can be traced back to the game Core War, in which computer programs had to compete with each other and try to stop the opponent from executing. It turned out that one of the winning strategies was to replicate as fast as possible, which had the result that the opponent was deprived of all computational resources. However, programs in the game 'core wars' did not mutate. Steen Rasmussen at Los Alamos National Laboratory took the idea from core wars one step further in his core world system. He introduced mutations, in the form of random changes in the instructions of the programs that were inhabiting the core world. However, Rasmussen did not observe the evolution of complex and stable programs. It turned out that the progamming language in which core world programs were written was very brittle, and more often than not mutations would completely destroy the functionality of a program. The first to solve the issue of program brittleness was Tom Ray with his Tierra system. Tierra was similar to core world. However, Ray made some key changes to the programming language such that mutations were much less likely to destroy a program. With these modifications, he observed for the first time computer programs that did indeed evolve in a meaningful and complex way. Later, Chris Adami, Titus Brown, and Charles Ofria started developing their Avida system, which was inspired by Tierra but had again some crucial differences. In Tierra, all programs were living in the same address space, and could potentially overwrite or otherwise interfere with each other. In Avida, on the other hand, each program lives in its own address space. Through this modification, experiments with Avida became much cleaner and easier to interpret than those with Tierra. With Avida, digital organisms research has started to get accepted as a valid contribution to evolutionary biology by a growing number of evolutionary biologists. Adami and coworkers have published in journals such as Nature and the Proceedings of the National Academy of Sciences (USA).

Systems for Digital Organisms Research

• Avida is a software platform to study the evolutionary biology of self-replicating and evolving computer programs (digital organisms). Avida was originally developed by Chris Adami, Titus Brown, and Charles Ofria, and was inspired by and inherits several of its properties from the Tierra system. The main difference between Avida and Tierra is that in Avida, every digital organism (that is, self-replicating computer program) lives in its own protected region of memory, and is executed by its own virtual CPU. By default, other digital organisms cannot access this memory space, neither for reading nor for writing, and cannot execute code that is not in their own memory space. A second major difference is that the virtual CPUs of different organisms can run at different speeds, such that one organism executes for example twice as many instructions in the same time interval than another organism. The speed at which a virtual CPU runs is determined by a number of factors, but most importantly, by the tasks that the organism performs: Tasks are logical computations that the organisms can carry out to reap extra CPU speed as bonus.
• Tierra is a computer simulation developed by ecologist Thomas S. Ray in the early 1990s in which computer programs compete for central processor unit (CPU) time and access to main memory. The computer programs in Tierra are evolvable and can mutate, self-replicate and recombine. Tierra is a frequently cited example of an artificial life model; in the metaphor of the Tierra, the evolvable computer programs can be considered as digital organisms which compete for energy (CPU time) and resources (main memory). The basic Tierra model has been used to experimentally explore in silico the basic processes of evolutionary and ecological dynamics. Processes such as the dynamics of punctuated equilibrium, host-parasite co-evolution and density dependent natural selection are amenable to investigation within the Tierra framework. A notable difference to more conventional models of evolutionary computation, such as genetic algorithms is that there is no explicit, or exogenous fitness function built into the model. Often in such models there is the notion of a function being "optimized"; in the case of Tierra, the fitness function is endogenous: there is simply survival and death. According to Ray and others this may allow for more "open-ended" evolution, in which the dynamics of the feedback between evolutionary and ecological processes can itself change over time. While the dynamics of Tierra are highly suggestive, the significance of the dynamics for real ecological and evolutionary behavior are still a subject of debate within the scientific community. Tierra is an abstract model, but any quantitative model is still subject to the same validation and verification techniques applied to more traditional mathematical models, and as such, has no special status. More detailed models in which more realistic dynamics of biological systems and organisms are incorporated is now an active research field.

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