Mikhail S. Burtsev

Evolution of cooperative strategies from first principles

One of the greatest challenges in the modern biological and social sciences is to understand the evolution of cooperative behaviour. General outlines of the answer to this puzzle are currently emerging as a result of developments in the theories of kin selection, reciprocity, multilevel selection and cultural group selection. The main conceptual tool used in probing the logical coherence of proposed explanations has been game theory, including both analytical models and agent-based simulations. The game-theoretic approach yields clear-cut results but assumes, as a rule, a simple structure of payoffs and a small set of possible strategies. Here we propose a more stringent test of the theory by developing a computer model with a considerably extended spectrum of possible strategies. In our model, agents are endowed with a limited set of receptors, a set of elementary actions and a neural net in between. Behavioural strategies are not predetermined; instead, the process of evolution constructs and reconstructs them from elementary actions. Two new strategies of cooperative attack and defence emerge in simulations, as well as the well-known dove, hawk and bourgeois strategies. Our results indicate that cooperative strategies can evolve even under such minimalist assumptions, provided that agents are capable of perceiving heritable external markers of other agents.

Theory of functional systems, adaptive critics and neural networks

We propose a general scheme of intelligent adaptive control system based on the Petr K. Anokhins theory of functional systems. This scheme is aimed at controlling adaptive purposeful behavior of an animat (a simulated animal) that has several natural needs (e.g., energy replenishment, reproduction). The control system consists of a set of hierarchically linked functional systems and enables predictive and goal-directed behavior. Each functional system includes a neural network based adaptive critic design. We also discuss schemes of prognosis, decision making, action selection and learning that occur in the functional systems and in the whole control system of the animat.

A new design for a green calcium indicator with a smaller size and a reduced number of calcium-binding sites

Genetically encoded calcium indicators (GECIs) are mainly represented by two- or one-fluorophore-based sensors. One type of two-fluorophore-based sensor, carrying Opsanus troponin C (TnC) as the Ca2+-binding moiety, has two binding sites for calcium ions, providing a linear response to calcium ions. One-fluorophore-based sensors have four Ca2+-binding sites but are better suited for in vivo experiments. Herein, we describe a novel design for a one-fluorophore-based GECI with two Ca2+-binding sites. The engineered sensor, called NTnC, uses TnC as the Ca2+-binding moiety, inserted in the mNeonGreen fluorescent protein. Monomeric NTnC has higher brightness and pH-stability in vitro compared with the standard GECI GCaMP6s. In addition, NTnC shows an inverted fluorescence response to Ca2+. Using NTnC, we have visualized Ca2+ dynamics during spontaneous activity of neuronal cultures as confirmed by control NTnC and its mutant, in which the affinity to Ca2+ is eliminated. Using whole-cell patch clamp, we have demonstrated that NTnC dynamics in neurons are similar to those of GCaMP6s and allow robust detection of single action potentials. Finally, we have used NTnC to visualize Ca2+ neuronal activity in vivo in the V1 cortical area in awake and freely moving mice using two-photon microscopy or an nVista miniaturized microscope.

Project Animat Brain: Designing the Animat Control System on the Basis of the Functional Systems Theory

The paper proposes the framework for an animat control system (the Animat Brain) that is based on the Petr K. Anokhins theory of functional systems. We propose the animat control system that consists of a set of functional systems (FSs) and enables predictive and purposeful behavior. Each FS consists of two neural networks: the actor and the predictor. The actors are intended to form chains of actions and the predictors are intended to make prognoses of future events. There are primary and secondary repertoires of behavior: the primary repertoire is formed by evolution; the secondary repertoire is formed by means of learning. This paper describes both principles of the Animat Brain operation and the particular model of predictive behavior in a cellular landmark environment.

Measuring the Dynamics of Artificial Evolution

This paper presents results of measuring evolution in a simple ALife system. Interpretation of these results is based on the notion of dynamical systems. This approach enables the discovery of periods of high evolutionary activity, which can be treated as evolutionary transitions. Attempts were also made to locate possible cycles of trajectory in the genome phase space, and it was concluded that there were no such cycles. These results demonstrate the usefulness of a dynamical systems approach in analyzing the dynamics of artificial evolution and provide suggestions for further development.

Model of Evolutionary Emergence of Purposeful Adaptive Behavior. The Role of Motivation

The process of evolutionary emergence of purposeful adaptive behavior is investigated by means of computer simulations. The model proposed implies that there is an evolving population of simple agents, which have two natural needs: energy and reproduction. Any need is characterized quantitatively by a corresponding motivation. Motivations determine goal-directed behavior of agents. The model demonstrates that purposeful behavior does emerge in the simulated evolutionary processes. Emergence of purposefulness is accompanied by origin of a simple hierarchy in the control system of agents.

Tracking the trajectories of evolution

This article proposes a method of visualizing and measuring evolution in artificial life simulations. The evolving population of agents is treated as a dynamical system. The proposed method is inspired by the notion of trajectory. The article provides examples of tracking of trajectories of evolutionary systems in the spaces of genotypes, strategies, and some global characteristics. Visualization similar to a bifurcation diagram is used to represent results of a series of simulations.

Artificial life meets anthropology: a case of aggression in primitive societies

One of the greatest challenges in the modern biological and social sciences has been to understand the evolution of altruistic and cooperative behaviors. General outlines of the answer to this puzzle are currently emerging as a result of developments in the evolutionary theories of multilevel selection, cultural group selection, and strong reciprocity. In spite of the progress in theory there is shortage of studies devoted to the connection of theoretical results to the real social systems. This paper presents the model of cooperation which is based on assumptions of heritable markers, constrained resource, and local interactions. Verification of model’s predictions with the real data on aggression in archaic egalitarian societies has demonstrated that initial modeling assumptions are acceptable as major factors of social evolution for these societies.

Simulation of the evolution of aging: effects of aggression and kin-recognition

Current biological theory has no commonly accepted view on the phenomenon of aging. On the one hand it is considered as an inescapable degradation immanent to complex biological systems and on the other hand as outcome of evolution. At the moment, there are three major complementary theories of evolutionary origin of senescence - the programmed death theory, the mutation accumulation theory, and the antagonistic pleiotropy theory. The later two are rather extensively studied theoretically and computationally but the former one received less attention. Here we present computer multi-agent model of aging evolution compatible with theories of programmed death and mutation accumulation. In our study we test how presence of aggression and kin-recognition affects evolution of age dependent suicide which is an analog of programmed death in the model.