The Dynamic Genome: A Darwinian Approach

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It is also important to add that there are several ways of influencing ROM by organism, without writing anything in it, but changing it. The role of sexual reproduction happens to be, in this context, an enhanced mean of forgetting. These endosymbionts also have their ROM, which is in this way selected by the organism. In case of genetic mutation, it is quite improbable that a concrete mutation could appear simultaneously in many organisms of a population. For phenotypic changes, vice versa, it could be quite usual that a particular change takes place simultaneously in many specimens since the genome and [p.

New evolutionary findings could be rapid since these are primarily a result of the functioning of organisms, a new or changed way of using the ROM by organisms. Corresponding genetic changes could be treated as after-effects of the morphological and behavioural change. Rapid morphological changes in speciation, as described by punctualists, and gradual genetic changes, as described by molecular evolutionists, are thus found to be in correspondence, since the latter follow the former.

Dynamic Genome Darwinian Approach by Antonio Fontdevila

In the existing models of Darwinian theory of evolution synthetic theory of evolution , the organism is not considered to have a multi-level structure with independent activity and a possibility to use its genome in various ways. Assuming the organisms to have activity, we find the autogenetic theory of evolution work.

Can Darwinism revolutionize AI?

Darwinian theory of evolution happens to be a special case of the autogenetic theory of evolution, assuming the organism to be very simple and passive. The main material for evolution is phenotypic variability. If phenotype and genotype are strongly connected i. If phenotype and genotype are more or less uncoupled due to plasticity, then the directional changes are phenotypic, and genetic variability is of minor importance.

An evolutionary change is like finding of a new melody by a player - the organism. It has a number of ways to keep this melody so long that it could be fixed by the stochastic changes of the genome. Another important aspect besides the Baldwin effect and its consequences described above which consequences are rarely considered, is the individuality of almost every single genome.

The size of any genome is so large, and the modifications particularly in case of sexual reproduction , although rare, are nevertheless frequent enough to make each genome individual. The interconnectedness of the processes in the cells results in the individuality of the context in which the 'products' of genes work; i.

Holdrege, Thus, no gene can have a constant meaning. Therefore, what has been selected for in one generation may not have the same meaning in the next one, which, in an extreme case, may turn selection itself quite senseless. In Fisher's theorems of natural selection Fisher, one can notice an unspoken assumption that reproduction is transitive.

However, because of the [p. If A , B and C mark a particular allele considering here its primary structure only in three sequential generations, the assumption of transitivity is still valid. And since natural selection acts just on phenotypes, Fisher's theorems cannot be used for describing that. Or, to be more correct, they rely on an unrealistic assumption. Due to the individuality of genotypes, the transitivity, thus, fails even without including the aspects of context cf.

Explaining the phenomenon of 'phenocopies' i. However, what we have here is much more than plasticity. The reason is that 'norm of reaction' is a term, which principally cannot have a finite description for any genotype. Expressing this in a more physical language: the boundary conditions for an organism in natural circumstances are indeterminable.

The dynamic genome : a Darwinian approach

A description of plasticity would be analogous to listing of all the possible meanings, which a particular word can have in all possible conditions. Thus, it cannot be viewed as an operational term. This also means that plasticity, generally, cannot be used as a measurable property of a genotype. According to the neo-Darwinian mechanism of evolution, the complex structure of organism does not play a direct role in the mechanism of an evolutionary change, i.

In most population-genetic models, a change in genotype and a change in phenotype are considered as being simultaneous. Hierarchy is thus still not represented in the models of evolution.

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However, if organism itself is regarded as the subject of evolution Weingarten, , and the organism's search turns out to be a direct factor of evolution, the hierarchical and multi-level structure of organism becomes inevitably considered in the mechanisms of evolution Salthe, ; This view is leading to a possible 'cognitive turn in biology' cf.

Hoffmeyer, The possibility of solving several existing profound controversies in the theory of biology through considering the hierarchical structure of organism was proposed by E. Oldekop already. The recent work by E. Lamb ; Jablonka et al. In order to explain the relationship between natural selection and the mechanism described above, we need a very clear definition of natural selection. Assuming that natural selection necessarily requires difference in the survival i. Thus, if the offspring of two genotypically distinguishable sets of organisms have the same percentage of non-viable organisms e.

Natural selection can certainly be effective if the selective factor e. But if the population is permanently large, then natural selection cannot be very effective; Baldwinian mechanism, however, may still effectively work and, consequently, evolution may continue. If a broader definition for natural selection is used, then Baldwinian mechanism still includes natural selection since some genotypes die anyway, e.

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It is quite difficult to find a direct experimental or empirical evidence which could distinguish between the selectionist and autogenetic in the version presented here theory of evolution. The main idea is that the neo-Darwinian theory of evolution including the theory of population genetics and behavioural ecology formally considers phenotype and genotype to be existing and functioning simultaneously. It means that no important theoretical conclusions as far as I know, of course have been drawn, which could result from the time difference of phenotypic and genotypic changes.

In this sense, what I propose is actually not a refutation of the neo-Darwinian theory, but a more general view to which a possible time difference is added. When the time difference is becoming equal to zero, we can get exactly the existing theory as a special case. Even research carried out into the role of the plasticity of phenotype in evolution has not assumed the difference in time, i.

The plasticity, if existing, is usually assumed to be a result of particular genes. It could be analysed in this way, but then we have to accept the possibility that the genome is used in several different ways by the phenotype.

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The other point is that the existing neo-Darwinian theory assumes the reproduction of organisms and genes to be structurally transitive. According to contemporary knowledge, changes in context make reproduction intransitive.

It follows that we need a broader theory. However, this in its turn means that we can get the neo-Darwinian theory as a special case, namely, for the situations when transitivity is assumed. There are also several paradoxes, which were not easy to solve in the framework of the classical approach.

Only a very small piece of genome could be produced as an optimal one. This means that at the given time of the evolution of life on the Earth, the number of generations and the number of organisms born give the maximum estimation of the different genotypes ever built and checked for their survival. This number is seemingly lower than 4 50 , which means that no longer than one bases DNA-sequence could have been checked by natural selection for all its possible combinations of primary structure. In case of sexual reproduction, almost every individual has its own genotype which has never existed before.

Nevertheless, a remarkable part of offspring is viable. This paradox may not be easy to solve from the point of view of strong neo-Darwinism, since, strictly speaking, the viability of a unique genotype is unpredictable. Also, if many of new genotypes are viable, it means that natural selection is, at least, not intensive.

The offspring, which is genetically different from the parent, does not, evidently, contribute to the fitness of the parent's genotype. The views described here are close or complementary to the views of Eva Jablonka, Richard C. Strohman , and many others. Below, some principal differences between neo-Darwinism and post-Darwinism are shortly pointed out:. According to Baer : "Ohne Zweifel ist auch der Organismus ein mechanischer Apparat, eine Maschine, die sich selbst aufbaut. The evolution of organisms, as well as of language, is autogenetic evolution.

The statement that the evolution of organisms or language - Bichakjian, can be Darwinian is apparently true when applying only very general features of the Darwinian mechanism, when only diversification, genealogy and historical replacement are considered. A closer consideration indicates that the mechanisms of dialogue biparentality or mutual recognition and autogenetics become applicable, and this means that the mechanism is post-Darwinian.

However, according to E. Mayr "Darwinism is not a simple theory that is either true or false but is rather a highly complex research [p. Similar is the conclusion of K. Researchers use this approach to study life as we know it, but also life as it might be otherwise.

Open-ended evolution studies often incorporate artificial organisms like those in artificial life studies, and observe the evolution of these organisms under conditions like those that produced biological evolution — namely, reproduction based on direct actions within the environment finding mates, obtaining enough food to survive and reproduce, evading predators, etc. The field of open-ended evolution is relatively small compared to that of deep learning but is actually a notably older field, with pioneering researchers such as Charles Ofria, Jordan Pollack, Risto Miikkulainen, and their students several of whom are now leaders in the field having spent decades in the trenches.

For a more complete description of the history and prospects of open-endedness, see this post from Lehman, Stanley, and Soros, and this paper by Jeff Clune [13]. Can artificial organisms evolved in open-ended environments lead to advancements in AI models agents? Addressing the first factor, environments must house a diversity of agents of different species with distinct needs and capabilities such that co-evolution of species might lead to collaboration within species — a likely prerequisite for the evolution of human-level intelligence.

Dynamic Genome: A Darwinian Approach - Oxford Scholarship

While co-evolution has led to faster and faster cheetahs and impalas, it has also led to intelligent social behavior in wolves, as is exhibited by coordinated hunting in packs. Indeed, a very recent study by OpenAI demonstrates the emergence of complex interactive behaviors among agents trained by reinforcement learning, despite a seemingly impoverished reward system.

Notably, rewards were given for team akin to species performance, not individual performance — much like all the wolves in a pack are rewarded when a large kill is made. There is an important contrast between reinforcement learning and evolutionary computation that should be mentioned here.

In nature, reinforcement learning serves as a model for how animals learn during their lifetime. However, many animal capabilities are acquired through evolution and bestowed during prenatal development or quickly after birth. An extreme example of innateness is the rapidity with which some animals gain complex motor control after birth within minutes. The bottom line is that biological organism are pre-wired for many abilities.

Constructing AI agents with more general, real-world capabilities might be achieved by first evolving agents to have baseline innate knowledge physics, emotions, fundamental desires, etc. As previously stated, the second factor we believe to be critical for evolving intelligent agents is a rich, diverse, and dynamic environment. Such an environment contains niche conditions across time and space that certain genetic mutations may prove advantageous within, but would be washed out of the species over subsequent generations if the environment was homogeneous.

In turn, the mutated, advantageous phenotypes may also prove to be advantageous in a different niche environment, which organisms could come across due to self-driven movement or due to changes in their local environment e. This is somewhat akin to the previously discussed quality-diversity approaches in genetic algorithms. Beyond what has already been stated, we list here a few aspects of agents, agent environments, and genetic algorithms that we speculate could promote the evolution of agents with capabilities beyond those of current AI models.

Some of the listed agent aspects may evolve naturally if the conditions support this, but they could also be imposed directly to accelerate evolution toward the end goal of general artificial intelligence.

The Dynamic Genome: A Darwinian Approach The Dynamic Genome: A Darwinian Approach
The Dynamic Genome: A Darwinian Approach The Dynamic Genome: A Darwinian Approach
The Dynamic Genome: A Darwinian Approach The Dynamic Genome: A Darwinian Approach
The Dynamic Genome: A Darwinian Approach The Dynamic Genome: A Darwinian Approach
The Dynamic Genome: A Darwinian Approach The Dynamic Genome: A Darwinian Approach
The Dynamic Genome: A Darwinian Approach The Dynamic Genome: A Darwinian Approach

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