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PubMed1998

Cooperative knowledge evolution: a construction-integration approach to knowledge discovery in medicine.

In this paper, we perform a cognitive analysis of knowledge discovery processes. As a result of this analysis, the construction-integration theory is proposed as a general framework for developing cooperative knowledge evolution systems. We thus suggest that for the acquisition of new domain knowledge in medicine, one should first construct pluralistic views on a given topic which may contain inconsistencies as well as redundancies. Only thereafter does this knowledge become consolidated into a situation-specific circumscription and the early inconsistencies become eliminated. As a proof for the viability of such knowledge acquisition processes in medicine, we present the IDEAS system, which can be used for the intelligent documentation of adverse events in clinical studies. This system provides a better documentation of the side-effects of medical drugs. Thereby, knowledge evolution occurs by achieving consistent explanations in increasingly larger contexts (i.e., more cases and more pharmaceutical substrates). Finally, it is shown how prototypes, model-based approaches and cooperative knowledge evolution systems can be distinguished as different classes of knowledge-based systems.

Artificial Intelligence↗
PubMed2000

Ecological constraints, life history traits and the evolution of cooperative breeding.

The ecological constraints hypothesis is widely accepted as an explanation for the evolution of delayed dispersal in cooperatively breeding birds. Intraspecific studies offer the strongest support. Observational studies have demonstrated a positive association between the severity of ecological constraints and the prevalence of cooperation, and experimental studies in which constraints on independent breeding were relaxed resulted in helpers moving to adopt the vacant breeding opportunities. However, this hypothesis has proved less successful in explaining why cooperative breeding has evolved in some species or lineages but not in others. Comparative studies have failed to identify ecological factors that differ consistently between cooperative and noncooperative species. The life history hypothesis, which emphasizes the role of life history traits in the evolution of cooperative breeding, offers a solution to this difficulty. A recent analysis showed that low adult mortality and low dispersal predisposed certain lineages to show cooperative behaviour, given the right ecological conditions. This represents an important advance, not least by offering an explanation for the patchy phylogenetic distribution of cooperative breeding. We discuss the complementary nature of these two hypotheses and suggest that rather than regarding life history traits as predisposing and ecological factors as facilitating cooperation, they are more likely to act in concert. While acknowledging that different cooperative systems may be a consequence of different selective pressures, we suggest that to identify the key differences between cooperative and noncooperative species, a broad constraints hypothesis that incorporates ecological and life history traits in a single measure of 'turnover of breeding opportunities' may provide the most promising avenue for future comparative studies. Copyright 2000 The Association for the Study of Animal Behaviour.

Journal Article↗
PubMed2002

A new approach for the cooperative chemical evolution of nucleic acids and proteins under the primitive earth environment.

In order to evaluate cooperative chemical evolution of nucleic acids and proteins, we have examined possible activity of thermal copolymers of amino acids (TCAA) for prebiotic formation and degradation of RNA. Several types of TCAA involving aromatic amino acids were prepared and the influence on the template-directed formation of oligoguanylate and prebiotic ribonuclease activity were kinetically studied.

Chromatography, High Pressure Liquid↗
PubMed2003

Perspective: repression of competition and the evolution of cooperation.

Repression of competition within groups joins kin selection as the second major force in the history of life shaping the evolution of cooperation. When opportunities for competition against neighbors are limited within groups, individuals can increase their own success only by enhancing the efficiency and productivity of their group. Thus, characters that repress competition within groups promote cooperation and enhance group success. Leigh first expressed this idea in the context of fair meiosis, in which each chromosome has an equal chance of transmission via gametes. Randomized success means that each part of the genome can increase its own success only by enhancing the total number of progeny and thus increasing the success of the group. Alexander used this insight about repression of competition in fair meiosis to develop his theories for the evolution of human sociality. Alexander argued that human social structures spread when they repress competition within groups and promote successful group-against-group competition. Buss introduced a new example with his suggestion that metazoan success depended on repression of competition between cellular lineages. Maynard Smith synthesized different lines of thought on repression of competition. In this paper, I develop simple mathematical models to illustrate the main processes by which repression of competition evolves. With the concepts made clear, I then explain the history of the idea. I finish by summarizing many new developments in this subject and the most promising lines for future study.

Animals↗
PubMed2006

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.

Animals↗
PubMed1999

Evolution of cooperation in spatially structured populations

Using a spatial lattice model of the Iterated Prisoner's Dilemma we studied the evolution of cooperation within the strategy space of all stochastic strategies with a memory of one round. Comparing the spatial model with a randomly mixed model showed that (1) there is more cooperative behaviour in a spatially structured population, (2) PAVLOV and generous variants of it are very successful strategies in the spatial context and (3) in spatially structured populations evolution is much less chaotic than in unstructured populations. In spatially structured populations, generous variants of PAVLOV are found to be very successful strategies in playing the Iterated Prisoner's Dilemma. The main weakness of PAVLOV is that it is exploitable by defective strategies. In a spatial context this disadvantage is much less important than the good error correction of PAVLOV, and especially of generous PAVLOV, because in a spatially structured population successful strategies always build clusters. Copyright 1999 Academic Press.

Journal Article↗
PubMed2004

Evolution of cooperation: two for one?

How can cooperation thrive in a selfish world? Recent evolution experiments show how bacteria themselves can generate conditions that make cooperation a winning strategy. At least in the short term.

Animals↗
PubMed2001

Evolution of cooperation through indirect reciprocity.

How can cooperation through indirect reciprocity evolve and what would it be like? This problem has previously been studied by simulating evolution in a small group of interacting individuals, assuming no gene flow between groups. In these simulations, certain 'image scoring' strategies were found to be the most successful. However, analytical arguments show that it would not be in an individual's interest to use these strategies. Starting with this puzzle, we investigate indirect reciprocity in simulations based on an island model. This has an advantage in that the role of genetic drift can be examined. Our results show that the image scoring strategies depend on very strong drift or a very small cost of giving help. As soon as these factors are absent, selection eliminates image scoring. We also consider other possibilities for the evolution of indirect reciprocity. In particular, we find that the strategy of aiming for 'good standing' has superior properties. It can be an evolutionarily stable strategy and, even if not, it usually beats image scoring. Furthermore, by introducing quality variation among individuals into the model, we show that the standing strategy can be quality revealing, adding a new dimension to indirect reciprocity. Finally, we discuss general problems with currently popular modelling styles.

Animals↗
PubMed2002

Solving the freeloaders paradox: Genetic associations and frequency-dependent selection in the evolution of cooperation among nonrelatives.

One of the enduring problems in the study of social evolution has been to understand how cooperation can be maintained in the presence of freeloaders, individuals that take advantage of the more cooperative members of groups they are eager to join. The freeloader problem has been particularly troublesome when groups consist of nonrelatives, and no inclusive fitness benefits accrue to individuals that contribute more heavily to communal activities. These theoretical difficulties, however, are not mirrored by the numerous examples of cooperative or even altruistic behaviors exhibited by groups of nonrelatives in nature (e.g., many human groups, communally nesting bees, multiple queen-founding ants, cellular slime molds, and social bacteria). Using a model in which cooperation and grouping tendencies are modeled as coevolving dynamical variables, I show that the freeloader problem can be addressed when group-size effects on fitness are considered explicitly. I show that freeloaders, whose presence is reflected in the development of linkage disequilibrium between grouping and cooperation, increase in frequency when rare, but are selected against when common due to the reduced productivity of the groups they overburden with their presence. Freeloader frequencies thus periodically rise and fall around an equilibrium shown here to be dynamic. These results highlight the importance of group-level effects in the origin and maintenance of sociality, illustrate the dynamic nature of equilibria when multiple levels of selection are involved, and provide a solution to the freeloaders paradox.

Biological Evolution↗
PubMed2001

The evolution of cooperative breeding through group augmentation.

Some individuals (helpers) in cooperatively breeding species provide alloparental care and often suppress their own reproduction. Kin selection is clearly an important explanation for such behaviour, but a possible alternative is group augmentation where individuals survive or reproduce better in large groups and where it therefore pays to recruit new members to the group. The evolutionary stability of group augmentation is currently disputed. We model evolutionarily stable helping strategies by following the dynamics of social groups with varying degrees of subordinate help. We also distinguish between passive augmentation, where a group member benefits from the mere presence of others, and active augmentation, where their presence as such is neutral or harmful, but where helping to recruit new group members may still be beneficial if they in turn actively provide help for the current reproductives ('delayed reciprocity'). The results show that group augmentation (either passive or active) can be evolutionarily stable and explain costly helping by non-reproductive subordinates, either alone or leading to elevated help levels when acting in concert with kin selection. Group augmentation can thus potentially explain the weak relationships between relatedness and helping behaviour that are observed in some cooperatively breeding species. In some cases, the superior mutualistic performance of cooperatively behaving groups can generate an incentive to stay and help which is strong enough to make ecological constraints unnecessary for explaining the stability of cooperatively breeding groups.

Animals↗
PubMed1989

A hierarchical model of the evolution of cooperation in cultural systems.

In this paper the following problem is addressed: "Under what conditions can a collection of individual organisms learn to cooperate when cooperation appears to outwardly degrade individual performance at the outset. In order to attempt a theoretical solution to this problem, data from a real world problem in anthropology is used. A distributed simulation model of this system was developed to assess its long term behavior using using an approach suggested by Zeigler (Zeigler, B.P., 1984, Multifaceted Modelling and Discrete Event Simulation (Academic Press, London)). The results of the simulation are used to show that although cooperation degrades the performance potential of each individual, it enhances the persistence of the individual's partial solution to the problem in certain situations."

Animals↗
PubMed2006

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.

Altruism↗
PubMed2004

The evolution of cooperation.

Darwin recognized that natural selection could not favor a trait in one species solely for the benefit of another species. The modern, selfish-gene view of the world suggests that cooperation between individuals, whether of the same species or different species, should be especially vulnerable to the evolution of noncooperators. Yet, cooperation is prevalent in nature both within and between species. What special circumstances or mechanisms thus favor cooperation? Currently, evolutionary biology offers a set of disparate explanations, and a general framework for this breadth of models has not emerged. Here, we offer a tripartite structure that links previously disconnected views of cooperation. We distinguish three general models by which cooperation can evolve and be maintained: (i) directed reciprocation--cooperation with individuals who give in return; (ii) shared genes--cooperation with relatives (e.g., kin selection); and (iii) byproduct benefits--cooperation as an incidental consequence of selfish action. Each general model is further subdivided. Several renowned examples of cooperation that have lacked explanation until recently--plant-rhizobium symbioses and bacteria-squid light organs--fit squarely within this framework. Natural systems of cooperation often involve more than one model, and a fruitful direction for future research is to understand how these models interact to maintain cooperation in the long term.

Algorithms↗
PubMed2006

A simple rule for the evolution of cooperation on graphs and social networks.

A fundamental aspect of all biological systems is cooperation. Cooperative interactions are required for many levels of biological organization ranging from single cells to groups of animals. Human society is based to a large extent on mechanisms that promote cooperation. It is well known that in unstructured populations, natural selection favours defectors over cooperators. There is much current interest, however, in studying evolutionary games in structured populations and on graphs. These efforts recognize the fact that who-meets-whom is not random, but determined by spatial relationships or social networks. Here we describe a surprisingly simple rule that is a good approximation for all graphs that we have analysed, including cycles, spatial lattices, random regular graphs, random graphs and scale-free networks: natural selection favours cooperation, if the benefit of the altruistic act, b, divided by the cost, c, exceeds the average number of neighbours, k, which means b/c > k. In this case, cooperation can evolve as a consequence of 'social viscosity' even in the absence of reputation effects or strategic complexity.

Altruism↗
PubMed2006

Evolution of cooperation by multilevel selection.

We propose a minimalist stochastic model of multilevel (or group) selection. A population is subdivided into groups. Individuals interact with other members of the group in an evolutionary game that determines their fitness. Individuals reproduce, and offspring are added to the same group. If a group reaches a certain size, it can split into two. Faster reproducing individuals lead to larger groups that split more often. In our model, higher-level selection emerges as a byproduct of individual reproduction and population structure. We derive a fundamental condition for the evolution of cooperation by group selection: if b/c > 1 + n/m, then group selection favors cooperation. The parameters b and c denote the benefit and cost of the altruistic act, whereas n and m denote the maximum group size and the number of groups. The model can be extended to more than two levels of selection and to include migration.

Animals↗
PubMed1981

The evolution of cooperation.

Cooperation in organisms, whether bacteria or primates, has been a difficulty for evolutionary theory since Darwin. On the assumption that interactions between pairs of individuals occur on a probabilistic basis, a model is developed based on the concept of an evolutionarily stable strategy in the context of the Prisoner's Dilemma game. Deductions from the model, and the results of a computer tournament show how cooperation based on reciprocity can get started in an asocial world, can thrive while interacting with a wide range of other strategies, and can resist invasion once fully established. Potential applications include specific aspects of territoriality, mating, and disease.

Animals↗