GeNeSys - sistema de co-evolución genética y neuro-memética para la auto-organización senso-motriz y conductual en una sociedad de robots

Bio-inspired computing can be used to model natural and social systems, including societies with cultural development. Currently, two positions on cultural evolution stand out: with and without replicators. The existence of memes, as cultural replicators, is still hypothetical, and it seems better to look for them in the brain, because they can only be: neuro-memes. In literature there are only two models inspired by the neuro-memetics, and culture evolves side by side with genetics, so it’s necessary to model a gene-culture co-evolution, with neuro-memes. Such a model would be used to help validate the neuro-memetics, on the one hand, and on the other hand, it would help to understand and heal serious problems in human societies. Here, a genetic and neuro-memetic co-evolutionary system was achieved, and a robotic society used it for survive by developing behavioural patterns as a cultural tradition.La computación bio-inspirada puede ser empleada para modelar sistemas naturales y sociales, entre los cuales están las sociedades con desarrollo cultural. En la actualidad, sobresalen dos posturas sobre la evolución cultural: con y sin replicadores. La existencia de memes, como replicadores culturales, es aún hipotética, y parece mejor buscarlos en el cerebro, porque solo pueden ser: neuro-memes. En la literatura hay apenas dos modelos inspirados en la concepción neuro-memética, y como la evolución cultural va de la mano con la genética, se requiere entonces modelar una co-evolución gene-cultura, basada en neuro-memes. Un modelo así, se usaría para ayudar a validar la hipótesis neuro-memética, por un lado, y por el otro, ayudaría a comprender y atender serias problemáticas en las sociedades humanas. Con este proyecto se logró un sistema de co-evolución genética y neuro-memética, que fue usado por una sociedad de robots para sobrevivir, desarrollando un comportamiento cultural.Magíster en Ingeniería de Sistemas y ComputaciónMaestrí

Game theoretic modeling and analysis : A co-evolutionary, agent-based approach

Ph.DDOCTOR OF PHILOSOPH

Belief revision via Lamarckian evolution

We present a system for performing belief revision in a multi-agent environment. The system is called GBR (Genetic Belief Revisor) and it is based on a genetic algorithm. In this setting, different individuals are exposed to different experiences. This may happen because the world surrounding an agent changes over time or because we allow agents exploring different parts of the world. The algorithm permits the exchange of chromosomes from different agents and combines two different evolution strategies, one based on Darwin's and the other on Lamarck's evolutionary theory. The algorithm therefore includes also a Lamarckian operator that changes the memes of an agent in order to improve their fitness. The operator is implemented by means of a belief revision procedure that, by tracing logical derivations, identifies the memes leading to contradiction. Moreover, the algorithm comprises a special crossover mechanism for memes in which a meme can be acquired from another agent only if the other agent has accessed the meme, i.e. if an application of the Lamarckian operator has read or modified the meme. Experiments have been performed on the n-queen problem and on a problem of digital circuit diagnosis. In the case of the n-queen problem, the addition of the Lamarckian operator in the single agent case improves the fitness of the best solution. In both cases the experiments show that the distribution of constraints, even if it may lead to a reduction of the fitness of the best solution, does not produce a significant reduction

Belief revision via Lamarckian evolution

We present a genetic algorithm for performing belief revision in a multi-agent environment. In this setting, different individuals are exposed to dierent experiences. This may happen because the world surrounding an agent changes over time or because we allow agents exploring dierent parts of the world. The algorithm permits the exchange of chromosomes from dierent agents and combines two dierent evolution strategies, one based on Darwin's and the other on Lamarck's evolutionary theory. Experiments on a problem of digital circuit diagnosis and on the n-queen problem show that the addition of the Lamarckian operator in the single agent case improves the tness of the best solution, even if in the digital circuit case the tness dierence is not signicant. Moreover, the experiments show that the distribution of constraints, even if it leads to a decrease of the tness of the best solution, does not produce a signicant dierenc

Belief Revision via Lamarckian Evolution

We present a system for performing belief revision in a multi-agent environment. The system is called GBR (Genetic Belief Revisor) and it is based on a genetic algorithm. In this setting, different individuals are exposed to different experiences. This may happen because the world surrounding an agent changes over time or because we allow agents exploring different parts of the world. The algorithm permits the exchange of chromosomes from different agents and combines two different evolution strategies, one based on Darwin's and the other on Lamarck's evolutionary theory. The algorithm therefore includes also a Lamarckian operator that changes the memes of an agent in order to improve their fitness. The operator is implemented by means of a belief revision procedure that, by tracing logical derivations, identifies the memes leading to contradiction. Moreover, the algorithm comprises a special crossover mechanism for memes in which a meme can be acquired from another agent only if the other agent has "accessed" the meme, i.e..

Darwin's new clothes: the Neo-Darwinian meta-logic of cultural evolution

This thesis examines the current impasse in cultural evolutionary theory, in which the insertion of morality into cultural evolution has compromised the discontinuous, multiscalar principles of neo-Darwinism, creating a moral-evolutionary continuum. I draw on post-structuralist criticality to displace the exclusionary implications of the anthropocentric explanatory continuum, and on the flaws of post—structuralism to clarify the logical necessity of discontinuous, multiscalarity for a neo-Darwinian conception of cultural evolution. In the biological sciences, the principles of Darwinism remain undisputed even though the explanatory scalar scope of neo-Darwinism has ‘expanded’ at least since the 1950s. In the humanities, there is no agreement either upon a set of workable concepts of evolution, or a concept of multiple, discontinuous explanatory scales. Discussions tend to focus on the extent to which Darwinism can account for familiar ‘social conditions’: moral practices and issues; the complex web of information ‘replicated’ through peoples’ actions; the ‘evolved’ mind and our capacity for verbal language and reflexive behaviour as the basis for explaining the products and outcomes of culture. A plastic ‘feedback’ dynamic is posited between bio—genetic fundamentals or analogies and differential cultural expression; between the syncretism of biogenetic—Darwinian operations and active Lamarkian principles of cultural change. The default on to a social position is inadequate because it privileges a short time-span perspective for explaining the longer time—span processes of culture. It neglects an examination of the friction inherent to the spatial-material context within which variation is produced, and disregards an assessment of the logic of scalar discontinuity in the differential and longer-term workings of culture. The logic of cultural evolutionary theory is persistently vitiated by the supposed necessity of the humanities to create a moral perspective which inserts a reductive scalar continuum in the study of cultural evolution