In this pithy and highly readable book, Brian Skyrms, a recognised authority on game and decision theory, investigates traditional problems of the social contract in terms of evolutionary dynamics. Game theory is skilfully employed to offer new interpretations of a wide variety of social phenomena, including justice, mutual aid, commitment, convention and meaning. The author eschews any grand, unified theory. Rather, he presents the reader with tools drawn from evolutionary game theory for the purpose of analysing and coming to understand (...) the social contract. The book is not technical and requires no special background knowledge. As such, it could be enjoyed by students and professionals in a wide range of disciplines: political science, philosophy, decision theory, economics and biology. (shrink)

The 'Evolution of Cooperation' addresses a simple yet age-old question; If living things evolve through competition, how can cooperation ever emerge? Despite the abundant evidence of cooperation all around us, there existed no purely naturalistic answer to this question until 1979, when Robert Axelrod famously ran a computer tournament featuring a standard game-theory exercise called The Prisoner's Dilemma. To everyone's surprise, the program that won the tournament, named Tit for Tat, was not only the simplest but the most "cooperative" entrant. (...) This unexpected victory proved that cooperation - one might even say altruism - is mathematically possible and therefore needs no hidden hand or divine agent to create and sustain it. A great roadblock to the understanding of all sorts of behavior was at last removed. The updated edition includes an extensive new chapter on cooperation in cancer cells and among terrorist organizations. (shrink)

Despite wide acceptance that the attributes of living creatures have appeared through a cumulative evolutionary process guided chiefly by natural selection, many human activities have seemed analytically inaccessible through such an approach. Prominent evolutionary biologists, for example, have described morality as contrary to the direction of biological evolution, and moral philosophers rarely regard evolution as relevant to their discussions. -/- The Biology of Moral Systems adopts the position that moral questions arise out of conflicts of interest, and that moral systems (...) are ways of using confluences of interest at lower levels of social organiation to deal with conflicts of interest at higher levels. Moral systems are described as systems of indirect reciprocity: humans gain and lose socially and reproductively not only by direct transactions, but also by the reputations they gain from the everyday flow of social interactions. -/- The author develops a general theory of human interests, using senescence and effort theory from biology, to help analye the patterning of human lifetimes. He argues that the ultimate interests of humans are reproductive, and that the concept of morality has arisen within groups because of its contribution to unity in the context, ultimately, of success in intergroup competition. He contends that morality is not easily relatable to universals, and he carries this argument into a discussion of what he calls the greatest of all moral problems, the nuclear arms race. (shrink)

A model is presented to account for the natural selection of what is termed reciprocally altruistic behavior. The model shows how selection can operate -against the cheater (non-reciprocator) in the system. Three instances of altruistic behavior are discussed, the evolution of which the model can explain: (1) behavior involved in cleaning symbioses; (2) warning cries in birds: and (3) human reciprocal altruism. Regarding human reciprocal altruism, it is shown that the details of the psychological system that regulates this altruism can (...) be explained by the model. Specifically, friendship,d islike, moralistic aggression, gratitude, sympathy, trust, suspicion, trustworthiness, aspects of guilt, and some forms of dishonesty and hypocrisy can be explained as important adaptations to regulate the altruistic system. Each individual human is seen as possessing altruistic and cheating tendencies, the expression of which is sensitive to developmental variables that were selected to set the tendencies at a balance appropriate to the local social and ecological environment. (shrink)

Game theory based on rational choice is compared with game theory based on evolutionary, or other adaptive, dynamics. The Nash equilibrium concept has a central role to play in both theories, even though one makes extremely strong assumptions about cognitive capacities and common knowledge of the players, and the other does not. Nevertheless, there are also important differences between the two theories. These differences are illustrated in a number of games that model types of interaction that are key ingredients for (...) any theory of the social contract. (shrink)

This contribution is part of the special series of Inaugural Articles by members of the National Academy of Sciences elected on April 27, 1999.

If it was a matter of hunting a deer, everyone well realized that he must remain faithful to his post; but if a hare happened to pass within reach of one of them, we cannot doubt that he would have gone off in pursuit of it without scruple..." Rousseau's story of the hunt leaves many questions open. What are the values of a hare and of an individual's share of the deer given a successful hunt? What is the probability that (...) the hunt will be successful if all participants remain faithful to the hunt? Might two deer hunters decide to chase the hare? (shrink)

The iterated Prisoner’s Dilemma has become the standard model for the evolution of cooperative behavior within a community of egoistic agents, frequently cited for implications in both sociology and biology. Due primarily to the work of Axelrod (1980a, 198Ob, 1984, 1985), a strategy of tit for tat (TFT) has established a reputation as being particularly robust. Nowak and Sigmund (1992) have shown, however, that in a world of stochastic error or imperfect communication, it is not TFT that finally triumphs in (...) an ecological model based on population percentages (Axelrod and Hamilton 1981), but ‘generous tit for tat’ (GTFT), which repays cooperation with a probability of cooperation approaching 1 but forgives defection with a probability of l/3. In this paper, we consider a spatialized instantiation of the stochastic Prisoner’s Dilemma, using two-dimensional cellular automata (Wolfram, 1984, 1986; Gutowitz, 1990) to model the spatial dynamics of populations of competing strategies. The surprising result is that in the spatial model it is not GIFT but still more generous strategies that are favored. The optimal strategy within this spatial ecology appears to be a form of ‘bending over backwards’, which returns cooperation for defection with a probability of 2/3 - a rate twice as generous as GTFT. (shrink)

We work with a large spatialized array of individuals in an environment of drifting food sources and predators. The behavior of each individual is generated by its simple neural net; individuals are capable of making one of two sounds and are capable of responding to sounds from their immediate neighbors by opening their mouths or hiding. An individual whose mouth is open in the presence of food is “fed” and gains points; an individual who fails to hide when a predator (...) is present is “hurt” by losing points. Opening mouths, hiding, and making sounds each exact an energy cost. There is no direct evolutionary gain for acts of cooperation or “successful communication” per se. In such an environment we start with a spatialized array of neural nets with randomized weights. Using standard learning algorithms, our individuals “train up” on the behavior of successful neighbors at regular intervals. Given that simple setup, will a community of neural nets evolve a simple language for signaling the presence of food and predators? With important qualifications, the answer is “yes.” In a simple spatial environment, pursuing individualistic gains and using partial training on successful neighbors, randomized neural nets can learn to communicate. (shrink)

Many situations in human life present choices between (a) narrowly preferred particular alternatives and (b) narrowly less preferred (or aversive) particular alternatives that nevertheless form part of highly preferred abstract behavioral patterns. Such alternatives characterize problems of self-control. For example, at any given moment, a person may accept alcoholic drinks yet also prefer being sober to being drunk over the next few days. Other situations present choices between (a) alternatives beneficial to an individual and (b) alternatives that are less beneficial (...) (or harmful) to the individual that would nevertheless be beneficial if chosen by many individuals. Such alternatives characterize problems of social cooperation; choices of the latter alternative are generally considered to be altruistic. Altruism, like self-control, is a valuable temporally-extended pattern of behavior. Like self-control, altruism may be learned and maintained over an individual's lifetime. It needs no special inherited mechanism. Individual acts of altruism, each of which may be of no benefit (or of possible harm) to the actor, may nevertheless be beneficial when repeated over time. However, because each selfish decision is individually preferred to each altruistic decision, people can benefit from altruistic behavior only when they are committed to an altruistic pattern of acts and refuse to make decisions on a case-by-case basis. (shrink)

We extend previous work by modeling evolution of communication using a spatialized genetic algorithm which recombines strategies purely locally. Here cellular automata are used as a spatialized environment in which individuals gain points by capturing drifting food items and are 'harmed' if they fail to hide from migrating predators. Our individuals are capable of making one of two arbitrary sounds, heard only locally by their immediate neighbors. They can respond to sounds from their neighbors by opening their mouths or by (...) hiding. By opening their mouths in the presence of food they maximize gains; by hiding when a predator is present they minimize losses. We consider the result a 'natural' template for benefits from communication; unlike a range of other studies, it is here only the recipient of communicated information that immediately benefits. (shrink)

Skyrms describes how evolutionary models are helping us understand unselfish or cooperative behaviour in humans and animals. Mechanisms which can stabilize cooperative behaviour are sensitive to population densities, however. This creates the need for agent-based evolutionary models which depict individual interactions, spatial locations, and stochastic effects. One such model suggests that hostile environments may provide conditions conducive to the emergence and stabilization of cooperative behaviour. In particular, simulations show that random extinctions can keep population densities low, provide ongoing colonization opportunities, (...) and insulate cooperative communities from invasion. Agent-based and population models play complementary roles in furthering our understanding evolutionary processes. (shrink)

In the spatialized Prisoner's Dilemma, players compete against their immediate neighbors and adopt a neighbor's strategy should it prove locally superior. Fields of strategies evolve in the manner of cellular automata (Nowak and May, 1993; Mar and St. Denis, 1993a,b; Grim 1995, 1996). Often a question arises as to what the eventual outcome of an initial spatial configuration of strategies will be: Will a single strategy prove triumphant in the sense of progressively conquering more and more territory without opposition, or (...) will an equilibrium of some small number of strategies emerge? Here it is shown, for finite configurations of Prisoner's Dilemma strategies embedded in a given infinite background, that such questions are formally undecidable: there is no algorithm or effective procedure which, given a specification of a finite configuration, will in all cases tell us whether that configuration will or will not result in progressive conquest by a single strategy when embedded in the given field. The proof introduces undecidability into decision theory in three steps: by (1) outlining a class of abstract machines with familiar undecidability results, by (2) modelling these machines within a particular family of cellular automata, carrying over undecidability results for these, and finally by (3) showing that spatial configurations of Prisoner's Dilemma strategies will take the form of such cellular automata. (shrink)

Human language is a unique ability. It sits apart from other systems of communication in two striking ways: it is syntactic, and it is learned. While most approaches to the evolution of language have focused on the evolution of syntax, this paper explores the computational issues that arise in shifting from a simple innate communication system to an equally simple one that is learned. Associative network learning within an observational learning paradigm is used to explore the computational difficulties involved in (...) establishing and maintaining a simple learned communication system. Because Hebbian learning is found to be sufficient for this task, it is proposed that the basic computational demands of learning are unlikely to account for the rarity of even simple learned communication systems. Instead, it is the problem of *observing* that is likely to be central -- in particular the problem of determining what meaning a signal is intended to convey. (shrink)