Systems-chemistry approach to prebiotic evolution

The puzzle of the origin of life is grand. A major challenge is to understand the transition from a mixture of molecules into an entity with basic life faculties, such as a protocell, capable of self-replication and inheritance. Two major schools tackle this problem: the genetic, or replicator-first approach, and the metabolism-first approach. The replicator-first approach focuses on a single self-perpetuating informational biopolymer, e.g., RNA, as the first step, and it is thus often referred to as the “RNA world”. In contrast, the metabolism-first approach focuses on a network of chemical reactions among simpler chemical components that became endowed with some reproductive characteristics as the first step that led to a protocell. The lipid world scenario, largely initiated by our laboratory, delineates a specific example of metabolism first. It suggests that spontaneously forming assemblies of relatively simple molecules, such as mutually interacting lipids, that resemble primitive metabolism, are capable of storing and transmitting information similar to sequence-based polymeric RNA, except that in this case it is compositional information that is at work. This thesis is about further exploration of the lipid world scenario, showing in more detail how a relatively simple chemical system can acquire features such as selection and evolution. This was accomplished by studying dynamical aspects of the graded autocatalysis replication domain (GARD) computer-simulation lipid world model, previously developed at our laboratory. GARD simulates the homeostatic growth of a compositional amphiphile assembly by reversible accretion from a buffered heterogeneous external pool. This process is governed by a network of mutually catalytic reactions, and exhibits quasi-stationary compositional states termed compotype, that may be regarded as GARD species. I have demonstrated that that such GARD species exhibit positive as well as negative selection, an important prerequisite of a minimally living system. I further showed that when the catalytic network becomes dominated by mutual catalysis, as opposed to self-catalysis, selection is enhanced. When studying the dynamics of large populations of GARD assemblies under constant population conditions, I rewardingly found that they exhibit dynamics similar to natural ecosystem populations, e.g. similes of competition or predator-prey dynamics. I was able to establish relationships between a compotype’s internal molecular parameters (e.g. its molecular diversity) and population ecology behavior. In a separate vein, I have developed a new approach towards observing open-ended evolution, which enables asking whether there is an optimal level of open endedness in prebiotic evolution. Finally, I was able to show clear similarities between GARD compotypes and quasispecies in the Eigen-Schuster model for evolution, further underlining GARD’s capacity as an alternative to RNA World. Taken together, these results uncover quantitative aspects of the GARD model which in turn contribute towards our understanding of the origin of life via the lipid world scenario

Task Allocation in Foraging Robot Swarms:The Role of Information Sharing

Autonomous task allocation is a desirable feature of robot swarms that collect and deliver items in scenarios where congestion, caused by accumulated items or robots, can temporarily interfere with swarm behaviour. In such settings, self-regulation of workforce can prevent unnecessary energy consumption. We explore two types of self-regulation: non-social, where robots become idle upon experiencing congestion, and social, where robots broadcast information about congestion to their team mates in order to socially inhibit foraging. We show that while both types of self-regulation can lead to improved energy efficiency and increase the amount of resource collected, the speed with which information about congestion flows through a swarm affects the scalability of these algorithms

Essays on the co-evolution between strategies and technologies

Sensitivity, Innovation Attitudes, and Perseverance as the Strategic Foundations of Exaptation. Functions, Modular Architectures, and Technological Evolvability. A Generalized NK-Framework to Study the Co-Evolution Between Industry Dynamics and Artefact’s Architecture. Local Technological Evolution & University-Industry Collaboration

Embodiment in Evolution and Culture

From its beginnings, the theory of evolution has unsettled fundamental anthropological assumptions about the place of human beings in nature. The integration of human origins into natural history by Darwinism was countered by the philosophical anthropologies of the 20th century. Their attempts were to hold on even more resolutely to the special status of humans as beings 'open towards the world'. Today, evolutionary and philosophical anthropology have moved closer together via the paradigm of embodiment. Building on embodied cognitive science, this volume aims to establish how far the human mind and human cultural cognition can be attributed to the structures of human existence, structures which have emerged in the course of evolution and have in turn been affected by culture. The traditional dualism of nature and culture is transformed into an explanation of an evolutionary process in which body and mind are understood to be intertwined and mutually constitutive

Artificial evolution with Binary Decision Diagrams: a study in evolvability in neutral spaces

This thesis develops a new approach to evolving Binary Decision Diagrams, and uses it to study evolvability issues. For reasons that are not yet fully understood, current approaches to artificial evolution fail to exhibit the evolvability so readily exhibited in nature. To be able to apply evolvability to artificial evolution the field must first understand and characterise it; this will then lead to systems which are much more capable than they are currently. An experimental approach is taken. Carefully crafted, controlled experiments elucidate the mechanisms and properties that facilitate evolvability, focusing on the roles and interplay between neutrality, modularity, gradualism, robustness and diversity. Evolvability is found to emerge under gradual evolution as a biased distribution of functionality within the genotype-phenotype map, which serves to direct phenotypic variation. Neutrality facilitates fitness-conserving exploration, completely alleviating local optima. Population diversity, in conjunction with neutrality, is shown to facilitate the evolution of evolvability. The search is robust, scalable, and insensitive to the absence of initial diversity. The thesis concludes that gradual evolution in a search space that is free of local optima by way of neutrality can be a viable alternative to problematic evolution on multi-modal landscapes

EvoEvo Deliverable 6.8: Final report

Final report of the EvoEvo project