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Distributed Self-regulation Induced by Negative Feedbacks in Ecological and Economic Systems

We consider an ecological system governed by Lotka-Volterra dynamics and an example of an economic system as a mesomarket with perfect competition. We propose a mechanism for cooperative self-regulation that enables the system under consideration to respond properly to changes in the environment. This mechanism is based on (1) active individual behavior of the system elements at each hierarchical level and (2) self-processing of information caused by the hierarchical organization. It is shown how the proposed mechanism suppresses nonlocal interaction of elements belonging to a particular level as mediated by higher levels.

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Extinction, diversity and survivorship of taxa in the fossil record

Using data drawn from large-scale databases, a number of interesting trends in the fossil record have been observed in recent years. These include the average decline in extinction rates throughout the Phanerozoic, the average increase in standing diversity, correlations between rates of origination and extinction, and simple laws governing the form of survivorship curves and the distribution of the lifetimes of taxa. In this paper we derive mathematically a number of relations between these quantities and show how these different trends are inter-related. We also derive a variety of constraints on the possible forms of these trends, such as limits on the rate at which extinction may decline and limits on the allowed difference between extinction and origination rates at any given time.

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The Structure of Adaptive Competition in Minority Games

In this paper we present results and analyses of a class of games in which heterogeneous agents are rewarded for being in a minority group. Each agent possesses a number of fixed strategies each of which are predictors of the next minority group. The strategies use a set of aggregate, publicly available information (reflecting the agents' collective previous decisions) to make their predictions. An agent chooses which group to join at a given moment by using one of his strategies. These games are adaptive in that agents can choose, at different points of the game, to exercise different strategies in making their choice of which group to join. We find, rather generally, that such systems evidence a phase change from a maladaptive, informationally efficient phase in which the system performs poorly at generating resources, to an inefficient phase in which there is an emergent cooperation among the agents, and the system more effectively generates resources. The best emergent coordination is achieved in a transition region between these two phases. This transition occurs when the dimension of the strategy space is of the order of the number of agents playing the game. We present explanations for this general behavior, based in part on an information theoretic analysis of the system and its publicly available information. We also propose a mean-field like model of the game which is most accurate in the maladaptive, efficient phase. In addition, we show that the best individual agent performance in the two different phases is achieved by sets of strategies with markedly different characteristics. We discuss implications of our results for various aspects of the study of complex adaptive systems.

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Power spectra of extinction in the fossil record

Recent Fourier analyses of fossil extinction data have indicated that the power spectrum of extinction during the Phanerozoic may take the form of 1/f noise, a result which, it has been suggested, could be indicative of the presence of "critical dynamics" in the processes giving rise to extinction. In this paper we examine extinction power spectra in some detail, using family-level data from a variety of different sources. We find that although the average form of the power spectrum roughly obeys the 1/f law, the spectrum can be represented more accurately by dividing it into two regimes: a low-frequency one which is well fit by an exponential, and a high-frequency one in which it follows a power law with a 1/f^2 form. We give explanations for the occurrence of each of these behaviours and for the position of the cross-over between them.

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Reproductive Tradeoffs In Uncertain Environments: Explaining The Evolution Of Cultural Elaboration

Dunnell's (1989) explanation for cultural elaboration proposed that elaboration could be a consequence of selection within uncertain environments. He developed the theory to the extent that it performed well explaining the distribution of elaboration at regional scales within eastern North America. More detailed studies require more detailed development of the theory, so that additional hypotheses and implications can be deduced. We draw upon theories of selection in fluctuating environments and portions of life history theory to propose a formal model of selection for "waste" in uncertain environments. We use agent-based simulation to explore the sufficiency of the theory for explaining the maintenance of high levels of elaboration within populations, and deduce novel implications for archaeological evidence usable by others to test the utility of Dunnell's model in specific localities.

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Market force, ecology and evolution

Markets have internal dynamics leading to excess volatility and other phenomena that are difficult to explain using rational expectations models. This paper studies these using a nonequilibrium price formation rule, developed in the context of trading with market orders. Because this is so much simpler than a standard inter-temporal equilibrium model, it is possible to study multi-period markets analytically. There price dynamics have second order oscillatory terms. Value investing does not necessarily cause prices to track values. Trend following causes short term trends in prices, but also causes longer-term oscillations. When value investing and trend following are combined, even though there is little linear structure, there can be boom-bust cycles,excess and temporally correlated volatility, and fat tails in price fluctuations. The long term evolution of markets can be studied in terms of flows of money. Profits can be decomposed in terms of aggregate pairwise correlations. Under reinvestment of profits this leads to a capital allocation model that is equivalent to a standard model in population biology. An investigation of market efficiency shows that patterns created by trend followers are more resistant to efficiency than those created by value investors, and that profit maximizing behavior slows the progression to efficiency. Order of magnitude estimates suggest that the timescale for efficiency is years to decades.

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The Evolutionary Biology of Ourselves: Unit Requirements and Organizational Change in United States History

Researchers have proposed that the distinction between so-called "simple" and "complex" societies can be expressed by an increase in the number of levels at which functional organization, interaction, and thus selection, operate. In spite of the obvious links between this suggestion and research into complex social organization amongst insects and other social animals, the levels of selection model has seen little use among anthropologists. We suggest that the primary reason for lack of research into the evolutionary causes of social complexity has been the lack of descriptive units with which we can examine phenotypic variation and heritability of social organization above the level of the organism. The goal of our paper, therefore, is to begin constructing descriptive units which map to meaningful models of multi-level selection. In order to demonstrate how these units are useful in a real dataset, we examine the functional changes involved in the United States economy over the last 100 years, a period of time characterized, we believe, by significant changes in the number and kinds of social aggregates functioning as "individuals" with respect to selection. Our preliminary analysis suggests that it is possible to measure changes in the scale at which functional integration occurs through published data, and that the multilevel selection model for complex society may possess considerable power for describing how selection of culturally transmitted variation occurs in complex societies.

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A Mathematical Model with Modified Logistic Approach for Singly-Peaked Population Processes

When a small number of individuals of organism of single species is confined in a closed space with limited amount of indispensable resources, their breading may start initially under suitable conditions, and after peaking, the population should go extinct as the resources are exhausted. Starting with the logistic equation and assuming that the carrying capacity of the environment is a function of the amount of resources, a mathematical model describing such pattern of population change is obtained. An application of this model to typical population records, that of deer herds by Scheffer (1951) and O'Roke and Hamerstrome (1948), yields estimations of the initial amount of indispensable food and its availability or nutritional efficiency which were previously unspecified.

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A General Approach to the Modelling of Trophic Chains

Based on the law of mass action (and its microscopic foundation) and mass conservation, we present here a method to derive consistent dynamic models for the time evolution of systems with an arbitrary number of species. Equations are derived through a mechanistic description, ensuring that all parameters have ecological meaning. After discussing the biological mechanisms associated to the logistic and Lotka-Volterra equations, we show how to derive general models for trophic chains, including the effects of internal states at fast time scales. We show that conformity with the mass action law leads to different functional forms for the Lotka-Volterra and trophic chain models. We use mass conservation to recover the concept of carrying capacity for an arbitrary food chain.

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The Evolutionary Unfolding of Complexity

We analyze the population dynamics of a broad class of fitness functions that exhibit epochal evolution---a dynamical behavior, commonly observed in both natural and artificial evolutionary processes, in which long periods of stasis in an evolving population are punctuated by sudden bursts of change. Our approach---statistical dynamics---combines methods from both statistical mechanics and dynamical systems theory in a way that offers an alternative to current ``landscape'' models of evolutionary optimization. We describe the population dynamics on the macroscopic level of fitness classes or phenotype subbasins, while averaging out the genotypic variation that is consistent with a macroscopic state. Metastability in epochal evolution occurs solely at the macroscopic level of the fitness distribution. While a balance between selection and mutation maintains a quasistationary distribution of fitness, individuals diffuse randomly through selectively neutral subbasins in genotype space. Sudden innovations occur when, through this diffusion, a genotypic portal is discovered that connects to a new subbasin of higher fitness genotypes. In this way, we identify innovations with the unfolding and stabilization of a new dimension in the macroscopic state space. The architectural view of subbasins and portals in genotype space clarifies how frozen accidents and the resulting phenotypic constraints guide the evolution to higher complexity.

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The Origin of the RNA World: a Kinetic Model

The aims of this paper are to propose, construct and analyse microscopic kinetic models for the emergence of long chains of RNA from monomeric beta-D-ribonucleotide precursors in prebiotic circumstances. Our theory starts out from similar but more general chemical assumptions to those of Eigen, namely that catalytic replication can lead to a large population of long chains. In particular, our models incorporate the possibility of (i) direct chain growth, (ii) template-assisted synthesis and (iii) catalysis by RNA replicase ribozymes, all with varying degrees of efficiency. However, in our models the reaction mechanisms are kept `open'; we do not assume the existence of closed hypercycles which sustain a population of long chains. Rather it is the feasibility of the initial emergence of a self-sustaining set of RNA chains from monomeric nucleotides which is our prime concern. We confront directly the central nonlinear features of the problem, which have often been overlooked in previous studies. Our detailed microscopic kinetic models lead to kinetic equations which are generalisations of the Becker-Doring system (BD) for the step-wise growth of clusters or polymer chains; they lie within a general theoretical framework which has recently been successfully applied to a wide range of complex chemical problems. In fact, the most accurate model we consider has BD aggregation terms, together with a general Smoluchowski fragmentation term to model the competing hydrolysis of RNA polymer chains. We conclude that, starting from reasonable initial conditions of monomeric nucleotide concentrations within a prebiotic soup and in an acceptable timescale, it is possible for a self-replicating subset of polyribonucleotide chains to be selected, while less efficient replicators become extinct.

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Evolution of genetic organization in digital organisms

We examine the evolution of expression patterns and the organization of genetic information in populations of self-replicating digital organisms. Seeding the experiments with a linearly expressed ancestor, we witness the development of complex, parallel secondary expression patterns. Using principles from information theory, we demonstrate an evolutionary pressure towards overlapping expressions causing variation (and hence further evolution) to sharply drop. Finally, we compare the overlapping sections of dominant genomes to those portions which are singly expressed and observe a significant difference in the entropy of their encoding.

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Mechanism of Self-regulation in a Simple Model of Hierarchically Organized Market

We propose a model for a market which structure is of the tree form. Each branch of the tree is composed by identical firms, its root (the branch of the first level) is formed by the firms producing raw material, and the branches of the last level are the retail outlets. The branching points (tree nodes) are micromarkets for firms forming branches connected with a given node. The prices and the production rate are controlled by the ballance in supply and demand, the competition is assumed to be perfect. We show that such a market functions perfectly: the prices are specified by the production expense only, whereas demand determines the production rate. We construct an efficiency functional which extremal gives the governing equations for the market. It turns out that this ideal market is degenerated with respect to its structure. It is shown, that such market functions ideally: the prices are determined by the costs on production of the goods, and the level of production of the goods of any kind defined only by demand for the goods of this sort.

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Replication Error and Time Evolution of a Self-Replicating System

A self-replicating system where the elements belonging to a solution category can replicate themselves by copying their own informations, is considered. The information carried by each element is defined by an element of all the n multiple tensor product of a base space that consists of m different base elements. We assume that in the replication the processes of copying each base information are the same and independent from one another and that the copying error distribution in each process is characterized by a small variation with a quite small mean value. Concentrating on the number fluctuation of the informations in the copying process, we analyze the time evolution of the system. We illustrate the change of averaged number of informations carried by system objects and the variation of the number distribution as a function of time. Especially, it is shown that the averaged number of information grows in general after large number of generations.

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Characterizing self-organization and coevolution by ergodic invariants

In addition to the emergent complexity of patterns that appears when many agents come in interaction, it is also useful to characterize the dynamical processes that lead to their self-organization. A set of ergodic invariants is identified for this purpose, which is computed in several examples, namely a Bernoulli network with either global or nearest-neighbor coupling, a generalized Bak-Sneppen model and a continuous minority model.

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Three sided complex adaptative systems

We introduce two three sided adaptative systems as toy models to mimic the exchange of commodities between buyers and sellers. These models are simple extensions of the minority game, exhibiting similar behaviour as well as some new features. The main difference between our two models is that in the first the three sides are equivalent while in the second, one choice appears as a compromise between the two other sides. Both models are investigated numerically and compared with the original minority game.

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Extremal Coupled Map Lattices

We propose a model for co-evolving ecosystems that takes into account two levels of description of an organism, for instance genotype and phenotype. Performance at the macroscopic level forces mutations at the microscopic level. These, in turn, affect the dynamics of the macroscopic variables. In some regions of parameter space, the system self-organises into a state with localised activity and power law distributions.

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Model of self-replicating cell capable of self-maintenance

We construct a simple model of a proto-cell that simulates a stochastic dynamics of abstract chemicals on a two-dimensional lattice. We assume that chemicals catalyze their reproduction through interaction with each other, and that between some chemicals repulsion occurs. We have shown that chemicals organize themselves into a cell-like structure that maintains its membranes dynamically. Further, we have obtained cells that can divide themselves automatically into daughter cells.

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