A computational model of symbiotic composition in evolutionary transitions

Abstract

Several of the major transitions in evolutionary history, such as the symbiogenic origin of eukaryotes from prokaryotes, share the feature that existing entities became the components of composite entities at a higher-level of organization. This composition of pre-adapted extant entities into a new whole is a fundamentally different source of variation from the gradual accumulation of small random variations, and it has some interesting consequences for issues of evolvability. Intuitively, the pre-adaptation of sets of features in reproductively independent specialists suggests a form of 'divide and conquer' decomposition of the adaptive domain. Moreover, the compositions resulting from one level may become the components for compositions at the next level, thus scaling-up the variation mechanism. In this paper, we explore and develop these concepts using a simple abstract model of symbiotic composition to examine its impact on evolvability. To exemplify the adaptive capacity of the composition model, we employ a scale-invariant fitness landscape exhibiting significant ruggedness at all scales. Whilst innovation by mutation and by conventional evolutionary algorithms becomes increasingly more difficult as evolution continues in this landscape, innovation by composition is not impeded as it discovers and assembles component entities through successive hierarchical levels.

Symbiosis, Synergy and Modularity: Introducing the Reciprocal Synergy Symbiosis Algorithm

“…Some have been aimed both at a computational biology audience (e.g. [21]) and problem solving in evolutionary computation (e.g. [5] [4]).…”

“…In the remainder of this section we review the Symbiogenic Evolutionary Adaptation Model (SEAM) [21], identify limitations and propose possible methods to address certain limitations of this approach with a new computational algorithm.…”

“…SEAM is an early evolutionary algorithm inspired by symbiogenesis [21]. It differs from typical evolutionary algorithms (EA) in several aspects.…”

“…The main loop of the algorithm operates as follows: two entities are picked at random, and evaluated in a number of contexts to determine if the pair should make a permanent symbiogenic alliance. A version of Pareto-dominance (see [21]) is used to make these decisions. If this is the case, the two symbionts are removed from the ecosystem and replaced with the chimera.…”

“…Finally, SEAM's performance in other Symbiosis, Synergy and Modularity: Introducing the Reciprocal Synergy Symbiosis Algorithm 3 problem domains is severely brittle: the utility of SEAM has only been demonstrated on a stylized hierarchical function, Hierarchical If-and-only-If (HIFF) [19]. Following [21] we develop a new symbiosis-inspired algorithm where individuals repeatedly test and make pairwise joins to compose larger and larger entities, resulting in problem solutions. As in prior work, we are also interested in understanding what symbiosis can offer us algorithmically, when compared with mutation and sexual recombination.…”