Design for a Darwinian Brain: Part 1. Philosophy and Neuroscience

Physical symbol systems are needed for open-ended cognition. A good way to understand physical symbol systems is by comparison of thought to chemistry. Both have systematicity, productivity and compositionality. The state of the art in cognitive architectures for open-ended cognition is critically assessed. I conclude that a cognitive architecture that evolves symbol structures in the brain is a promising candidate to explain open-ended cognition. Part 2 of the paper presents such a cognitive architecture.Comment: Darwinian Neurodynamics. Submitted as a two part paper to Living Machines 2013 Natural History Museum, Londo

Exponential Replication of Patterns in the Signal Tile Assembly Model

Chemical self-replicators are of considerable interest in the field of nanomanufacturing and as a model for evolution. We introduce the problem of self-replication of rectangular two-dimensional patterns in the practically motivated Signal Tile Assembly Model (STAM) [9]. The STAM is based on the Tile Assembly Model (TAM) which is a mathematical model of self-assembly in which DNA tile monomers may attach to other DNA tile monomers in a programmable way. More abstractly, four-sided tiles are assigned glue types to each edge, and self-assembly occurs when singleton tiles bind to a growing assembly, if the glue types match and the glue binding strength exceeds some threshold. The signal tile extension of the TAM allows signals to be propagated across assemblies to activate glues or break apart assemblies. Here, we construct a pattern replicator that replicates a two-dimensional input pattern over some fixed alphabet of size φ with O(φ) tile types, O(φ) unique glues, and a signal complexity of O(1). Furthermore, we show that this replication system displays exponential growth in n, the number of replicates of the initial patterned assembly

Before the Pandemic Ends: Making Sure This Never Happens Again

Introduction On 30 January 2020, the World Health Organization (WHO) declared a Global Health Emergency of international concern attendant to the emergence and spread of SARS-CoV-2, nearly two months after the first reported emergence of human cases in Wuhan, China. In the subsequent two months, global, national and local health personnel and infrastructures have been overwhelmed, leading to suffering and death for infected people, and the threat of socio-economic instability and potential collapse for humanity as a whole. This shows that our current and traditional mode of coping, anchored in responses after the fact, is not capable of dealing with the crisis of emerging infectious disease. Given all of our technological expertise, why is there an emerging disease crisis, and why are we losing the battle to contain and diminish emerging diseases? Part of the reason is that the prevailing paradigm explaining the biology of pathogen-host associations (coevolution, evolutionary arms races) has assumed that pathogens must evolve new capacities - special mutations – in order to colonize new hosts and produce emergent disease (e.g. Parrish and Kawaoka, 2005). In this erroneous but broadly prevalent view, the evolution of new capacities creates new opportunities for pathogens. Further, given that mutations are both rare and undirected, the highly specialized nature of pathogen-host relationships should produce an evolutionary firewall limiting dissemination; by those definitions, emergences should be rare (for a historical review see Brooks et al., 2019). Pathogens, however, have become far better at finding us than our traditional understanding predicts. We face considerable risk space for pathogens and disease that directly threaten us, our crops and livestock – through expanding interfaces bringing pathogens and hosts into increasing proximity, exacerbated by environmental disruption and urban density, fueled by globalized trade and travel. We need a new paradigm that explains what we are seeing. Additional section headers: The Stockholm Paradigm The DAMA Protocol A Sense of Urgency and Long-Term Commitment Reference

The evolution of cooperation and altruism--a general framework and a classification of models.

One of the enduring puzzles in biology and the social sciences is the origin and persistence of intraspecific cooperation and altruism in humans and other species. Hundreds of theoretical models have been proposed and there is much confusion about the relationship between these models. To clarify the situation, we developed a synthetic conceptual framework that delineates the conditions necessary for the evolution of altruism and cooperation. We show that at least one of the four following conditions needs to be fulfilled: direct benefits to the focal individual performing a cooperative act; direct or indirect information allowing a better than random guess about whether a given individual will behave cooperatively in repeated reciprocal interactions; preferential interactions between related individuals; and genetic correlation between genes coding for altruism and phenotypic traits that can be identified. When one or more of these conditions are met, altruism or cooperation can evolve if the cost-to-benefit ratio of altruistic and cooperative acts is greater than a threshold value. The cost-to-benefit ratio can be altered by coercion, punishment and policing which therefore act as mechanisms facilitating the evolution of altruism and cooperation. All the models proposed so far are explicitly or implicitly built on these general principles, allowing us to classify them into four general categories

Growth dynamics and the evolution of cooperation in microbial populations

Microbes providing public goods are widespread in nature despite running the risk of being exploited by free-riders. However, the precise ecological factors supporting cooperation are still puzzling. Following recent experiments, we consider the role of population growth and the repetitive fragmentation of populations into new colonies mimicking simple microbial life-cycles. Individual-based modeling reveals that demographic fluctuations, which lead to a large variance in the composition of colonies, promote cooperation. Biased by population dynamics these fluctuations result in two qualitatively distinct regimes of robust cooperation under repetitive fragmentation into groups. First, if the level of cooperation exceeds a threshold, cooperators will take over the whole population. Second, cooperators can also emerge from a single mutant leading to a robust coexistence between cooperators and free-riders. We find frequency and size of population bottlenecks, and growth dynamics to be the major ecological factors determining the regimes and thereby the evolutionary pathway towards cooperation.Comment: 26 pages, 6 figure

Ontology-guided data preparation for discovering genotype-phenotype relationships

International audienceComplexity of post-genomic data and multiplicity of mining strategies are two limits to Knowledge Discovery in Databases (KDD) in life sciences. Because they provide a semantic frame to data and because they benefit from the progress of semantic web technologies, bio-ontologies should be considered for playing a key role in the KDD process. In the frame of a case study relative to the search of genotype-phenotype relationships, we demonstrate the capability of bio-ontologies to guide data selection during the preparation step of the KDD process. We propose three scenarios to illustrate how domain knowledge can be taken into account in order to select or aggregate data to mine, and consequently how it can facilitate result interpretation at the end of the process

Computer Simulation on the Cooperation of Functional Molecules during the Early Stages of Evolution

It is very likely that life began with some RNA (or RNA-like) molecules, self-replicating by base-pairing and exhibiting enzyme-like functions that favored the self-replication. Different functional molecules may have emerged by favoring their own self-replication at different aspects. Then, a direct route towards complexity/efficiency may have been through the coexistence/cooperation of these molecules. However, the likelihood of this route remains quite unclear, especially because the molecules would be competing for limited common resources. By computer simulation using a Monte-Carlo model (with “micro-resolution” at the level of nucleotides and membrane components), we show that the coexistence/cooperation of these molecules can occur naturally, both in a naked form and in a protocell form. The results of the computer simulation also lead to quite a few deductions concerning the environment and history in the scenario. First, a naked stage (with functional molecules catalyzing template-replication and metabolism) may have occurred early in evolution but required high concentration and limited dispersal of the system (e.g., on some mineral surface); the emergence of protocells enabled a “habitat-shift” into bulk water. Second, the protocell stage started with a substage of “pseudo-protocells”, with functional molecules catalyzing template-replication and metabolism, but still missing the function involved in the synthesis of membrane components, the emergence of which would lead to a subsequent “true-protocell” substage. Third, the initial unstable membrane, composed of prebiotically available fatty acids, should have been superseded quite early by a more stable membrane (e.g., composed of phospholipids, like modern cells). Additionally, the membrane-takeover probably occurred at the transition of the two substages of the protocells. The scenario described in the present study should correspond to an episode in early evolution, after the emergence of single “genes”, but before the appearance of a “chromosome” with linked genes

Why and How Knowledge Discovery Can Be Useful for Solving Problems with CBR

International audienceIn this talk, we discuss and illustrate links existing between knowledge discovery in databases (KDD), knowledge representation and reasoning (KRR), and case-based reasoning (CBR). KDD techniques especially based on Formal Concept Analysis (FCA) are well formalized and allow the design of concept lattices from binary and complex data. These concept lattices provide a realistic basis for knowledge base organization and ontology engineering. More generally, they can be used for representing knowledge and reasoning in knowledge systems and CBR systems as well

Small Cofactors May Assist Protein Emergence from RNA World: Clues from RNA-Protein Complexes

It is now widely accepted that at an early stage in the evolution of life an RNA world arose, in which RNAs both served as the genetic material and catalyzed diverse biochemical reactions. Then, proteins have gradually replaced RNAs because of their superior catalytic properties in catalysis over time. Therefore, it is important to investigate how primitive functional proteins emerged from RNA world, which can shed light on the evolutionary pathway of life from RNA world to the modern world. In this work, we proposed that the emergence of most primitive functional proteins are assisted by the early primitive nucleotide cofactors, while only a minority are induced directly by RNAs based on the analysis of RNA-protein complexes. Furthermore, the present findings have significant implication for exploring the composition of primitive RNA, i.e., adenine base as principal building blocks

Co-Swarming and Local Collapse: Quorum Sensing Conveys Resilience to Bacterial Communities by Localizing Cheater Mutants in Pseudomonas aeruginosa

Background: Members of swarming bacterial consortia compete for nutrients but also use a co-operation mechanism called quorum sensing (QS) that relies on chemical signals as well as other secreted products (‘‘public goods’’) necessary for swarming. Deleting various genes of this machinery leads to cheater mutants impaired in various aspects of swarming cooperation. Methodology/Principal Findings: Pairwise consortia made of Pseudomonas aeruginosa, its QS mutants as well as B. cepacia cells show that a interspecies consortium can ‘‘combine the skills’ ’ of its participants so that the strains can cross together barriers that they could not cross alone. In contrast, deleterious mutants are excluded from consortia either by competition or by local population collapse. According to modeling, both scenarios are the consequence of the QS signalling mechanism itself. Conclusion/Significance: The results indirectly explain why it is an advantage for bacteria to maintain QS systems that can cross-talk among different species, and conversely, why certain QS mutants which can be abundant in isolated niches