Present conditions and selection pressures are irrelevant to the present design of orga-nisms and do not explain how or why organisms behave adaptively, when they do. To whatever non-chance extent organisms are behaving adaptively, it is 1) because of the operation of underlying adaptations whose present design is the product of selection in the past, and 2) because present conditions resemble past conditions in those specific ways made developmentally and functionally important by the design of those adap-tations. All adaptations evolved in response to the repeating elements of past environ-ments, and their structure reflects in detail the recurrent structure of ancestral envi-ronments. Even planning mechanisms (such as “consciousness”), which supposedly deal with novel situations, depend on ancestrally shaped categorization processes and are therefore not free of the past. In fact, the categorization of each new situation into evolutionarily repeating classes involves another kind of adaptation, the emotions, which match specialized modes of organismic operation to evolutionarily recurrent situations. The detailed statistical structure of these iterated systems of events is re-flected in the detailed structure of the algorithms that govern emotional state. For this

Group selection can overcome individual selection for selfishness and favor altruism if there is variation among the founders of spatially distinct groups, and groups with many altruists become substantially larger (or exist longer) than groups with few. Whether altruism can evolve in populations that do not have an alternation of local population growth and global dispersal (viscous populations) has been disputed for some time. Limited dispersal protects the altruists from the nonaltruists, but also hinders the export of altruism. In this article, we use the Pair Approximation technique (tracking the dynamics of pairs of neighbors instead of single individuals) to derive explicit invasion conditions for rare mutants in populations with limited dispersal. In such viscous populations, invading mutants form clusters, and ultimately, invasion conditions depend on the properties of such clusters. Thus there is selection on a higher level than that of the individual; in fact, invasion condi...

... Equation, a profound insight into the nature of selection and the basis for the modern theories of kin and group selection; (ii) the theory of games and animal behavior, based on the concept of the evolutionarily stable strategy; and (iii) the modern interpretation of Fisher’s fundamental theorem of natural selection, Fisher’s theorem being perhaps the most cited and least understood idea in the history of evolutionary genetics. This paper summarizes Price’s contributions and briefly outlines why, toward the end of his painful intellectual journey, he chose to focus his deep humanistic feelings and sharp,

Understanding the mechanisms that can lead to the evolution of cooperation through natural selection is a core problem in biology. Among the various attempts at constructing a theory of cooperation, game theory has played a central role. Here, we review models of cooperation that are based on two simple games: the Prisoner’s Dilemma, and the Snowdrift game. Both games are two-person games with two strategies, to cooperate and to defect, and both games are social dilemmas. In social dilemmas, cooperation is prone to exploitation by defectors, and the average payoff in populations at evolutionary equilibrium is lower than it would be in populations consisting of only cooperators. The difference between the games is that cooperation is not maintained in the Prisoner’s Dilemma, but persists in the Snowdrift game at an intermediate frequency. As a consequence, insights gained from studying extensions of the two games differ substantially. We review the most salient results obtained from extensions such as iteration, spatial structure, continuously variable cooperative investments, and multi-person interactions. Bridging the gap between theoretical and empirical research is one of the main challenges for future studies of cooperation, and we conclude by pointing out a number of promising natural systems in which the theory can be tested experimentally.

Kin selection arguments, based on Hamilton's (1964) concept of inclusive fitness, provide... of recipient, or other life history components of fitness, the fitness effects on each component are weighted by reproductive value. We illustrate this technique first in a homogeneous population, with examples of group competition and partial dispersal behaviour, and then in a class-structured population, with examples of sex allocation and altruism between age classes.

Abstract not found

In this paper I will discuss why (un) marked expressions typically get an (un)marked interpretation: Horn's division of pragmatic labor. It is argued that it is a conventional fact the we use language this way. This convention will be explained in terms of equilibria of signalling games introduced by Lewis (1969) but now in an evolutionary setting. I will also relate this signalling game analysis with Blutner's (2000) bi-directional optimality theory and with Parikh's (1991, 2000) game-theoretical analysis of successful communication.

Artificial life models of the evolution of communication have usually assumed either cooperative or competitive contexts. This paper presents a general model that covers signalling with and without conflicts of interest between signallers and receivers. Krebs & Dawkins (1984) argued that a conflict of interests will lead to an evolutionary arms race between manipulative signallers and sceptical receivers, resulting in ever more costly signals; whereas common interests will lead to cheap signals or "conspiratorial whispers ". Simple game-theoretic and evolutionary simulation models suggest that signalling will evolve only if it is in the interests of both parties. In a model where signallers may inform receivers as to the value of a binary random variable, if signalling is favoured at all, then signallers will always use the cheapest and the second-cheapest signal available. Costly signalling arms races do not get started. A more complex evolutionary simulation was constructed, featurin...

It is widely assumed that human learning and the structure of human languages are intimately related. This relationship is frequently suggested to be rooted in a language-specific biological endowment, which encodes universal, but arbitrary, principles of language structure (a universal grammar or UG). How might such a UG have evolved? We argue that UG could not have arisen either by biological adaptation or non-adaptationist genetic processes. The resulting puzzle concerning the origin of UG we call the logical problem of language evolution. Because the processes of language change are much more rapid than processes of genetic change, language constitutes a “moving target ” both over time and across different human populations, and hence cannot provide a stable environment to which UG genes could have adapted. We conclude that a biologically determined UG is not evolutionarily viable. Instead, the original motivation for UG—the mesh between learners and languages—arises because language has been shaped to fit the human brain, rather than vice versa. Following Darwin, we view language itself as a complex and interdependent “organism, ” which evolves under selectional pressures from human learning and processing mechanisms. That is, languages are themselves undergoing severe selectional pressure from each generation of language users and learners. This suggests that apparently arbitrary aspects of linguistic structure may result from general learning and processing biases, independent of language. We illustrate how this framework can integrate evidence from different literatures and methodologies to explain core linguistic phenomena, including binding constraints, word order universals, and diachronic language change. 1.

Group transport is performed in many natural systems and has become a canonical task for studying cooperation in robotics. We simulate a system of simple, insect-like robots that can move autonomously and grasp objects as well as each other. We use artificial evolution to produce solitary transport and group transport behaviors. We show that robots, even though not aware of each other, can be effective in group transport. Group transport can even be performed by robots that behave as in solitary transport. Still, robots engaged in group transport can benefit from behaving differently from robots engaged in solitary transport. The best group transport behaviors yielded by half of the evolutions let robots organize into self-assembled structures. This provides evidence that self-assembly can provide adaptive value to individuals that compete in an artificial evolution based on task performance. We conclude the article by discussing potential implications for evolutionary biology and robotics. Keywords group transport · solitary · social behavior · evolution of cooperation · self-assembly · autonomous robots · evolutionary robotics · swarm robotics · swarm intelligence · evolutionary biology 1