We present a general framework for analyzing the contribution to reproductive success of a behavioural action. An action may make a direct contribution to reproductive success, but even in the absence of a direct contribution it may make an indirect contribution by changing the animal's state. We consider actions over a period of time, and define a reward function that characterizes the relationship between the animal's state at the end of the period and its future reproductive success. Working back from (...) the end of the period using dynamic programming, the optimal action as a function of state and time can be found. The procedure also yields a measure of the cost, in terms of future reproductive success, of a suboptimal action. These costs provide us with a common currency for comparing activities such as eating and drinking, or eating and hiding from predators. The costs also give an indication of the robustness of the conclusions that can be drawn from a model. We review how our framework can be used to analyze optimal foraging decisions in a stochastic environment. We also discuss the modelling of optimal daily routines and provide an illustration based on singing to attract a mate. We use the model to investigate the features that can produce a dawn song burst in birds. State is defined very broadly so that it includes the information an animal has about its environment. Thus, exploration and learning can be included within the framework. (shrink)

A general framework for analysing the effects of variability and the effects of interruptions on foraging is presented. The animal is characterised by its level of energetic reserves, x. We consider behaviour over a period of time [0,T]. A terminal reward function R(x) determines the expected future reproductive success of an animal with reserves x at time T. For any state x at a time in the period, we give the animal a choice between various options and then constrain it (...) to follow a background strategy. The best option is the one that maximizes expected future reproductive success. Using this framework, we show that sensitivity to variability in amount of energy gained is logically distinct from sensitivity to variability in the time at which food is obtained. We also show that incorporating interruptions results in both a preference for variability in time and a preference for a reward followed by a delay as opposed to the same delay before the reward. (shrink)

Gould and Lewontin use San Marco, Venice, to criticise the adaptationist program in biology. Following their lead, the architectural term “spandrel” is now widely used in biology to denote a feature that is a necessary byproduct of other aspects of the organism. I review the debate over San Marco and argue that the spandrels are not necessary in the sense originally used by Gould and Lewontin. I conclude that almost all the claims that Gould makes about San Marco are wrong (...) and that it is reasonable to view the architectural spandrel as an adaptation. The spandrels example has not provided a good illustration of why adaptive explanations should be avoided. In fact, it can be used as an example of how adaptive explanations can be dismissed even when there is evidence in their favour. I also discuss the use of the concept of a spandrel in biology. (shrink)

It is shown that in a range of models, the probability that a forager dies from starvation is, to a good approximation, an exponential function of energy reserves. Using a time and energy budget for a 19g passerine, we explore the consequences, in terms of starvation and predation, of various levels of energy reserves. It is shown that there exists an optimal level L of reserves at which total mortality (starvation plus predation) is minimized. L increases when the environment deteriorates (...) as a result of a decrease in either temperature or mean gross gain or an increase in the mean search time. The effect of combined deteriorations is greater than the sum of their individual effects. At L, the probability of predation is much higher than the probability of starvation. A simple analytic model suggests that this result will be fairly general, but also indicates conditions under which the result might not hold. (shrink)

Behavioral ecologists often assume that natural selection will produce organisms that make optimal decisions. In the context of information processing, this means that the behavior of animals will be consistent with models from fields such as signal detection theory and Bayesian decision theory. We discuss work that applies such models to animal behavior and use the case of Bayesian updating to make the distinction between a description of behavior at the level of optimal decisions and a mechanistic account of how (...) decisions are made. The idea of ecological rationality is that natural selection shapes an animal's decision mechanisms to suit its environment. As a result, decision-making mechanisms may not perform well outside the context in which they evolved. Although the assumption of ecological rationality is plausible, we argue that the exact nature of the relationship between ecology and cognitive mechanism may not be obvious. (shrink)

Gangestad & Simpson review sexual selection theory and discuss their work on fluctuating asymmetry and mate preference in humans. We question some aspects of their account and mention problems with the data. We also suggest that more theoretical work on complex but realistic mating systems is required.

Rolls discusses various adaptive explanations of physiological processes and the emotions. We give a critical analysis of some of these from the perspective of behavioural ecology. While agreeing with the approach adopted by Rolls, we identify topics that could have been better presented by making use of the existing literature.

Gigerenzer, Todd, and the ABC Research Group give an interesting account of simple decision rules in a variety of contexts. I agree with their basic idea that animals use simple rules. In my commentary I concentrate on some aspects of their treatment of decision rules in behavioural ecology.

We concentrate on two aspects of the article by Pothos & Busemeyer (P&B): the relationship between classical and quantum probability and quantum probability as a basis for rational decisions. We argue that the mathematical relationship between classical and quantum probability is not quite what the authors claim. Furthermore, it might be premature to regard quantum probability as the best practical rational scheme for decision making.

John Maynard Smith was the founder of evolutionary game theory. He has also been the major influence on the direction of this field, which now pervades behavioural ecology and evolutionary biology. In its original formulation the theory had three components: a set of strategies, a payoff structure, and a concept of evolutionary stability. These three key components are still the basis of the theory, but what is assumed about each component is often different to the original assumptions. We review modern (...) approaches to these components. We emphasis that if a game is considered in isolation, and arbitrary payoffs are assumed, then the payoffs may not be consistent with other components of the system which are not modelled. Modelling the whole system, including not only the focal game, but also the future behaviour of the players and the behaviour of other population members, allows a consistent model to be constructed. We illustrate this in the case of two models of parental care, showing how linking a focal game to other aspects of the system alters what is predicted. (shrink)

I discuss various theoretical issues concerning maximizing, matching, and melioration. The model of addiction based on melioration has the key feature that a reduction in drag use increases both the value of drag-taking and the value of conventional activities. I found Heyman's target article stimulating. I don't feel competent to comment on drags but I do have some thoughts, both general and specific, on the theoretical issues.

In the theory outlined in the target article, an animal forages continuously, making sequential decisions in a world where the amount of food and its uncertainty are fixed, but delays are variable. These assumptions contrast with the risk-sensitive foraging theory and create a problem for comparing the predictions of this model with many laboratory experiments that do not make these assumptions.

Hebbian mechanisms are justified according to their functional utility in an evolutionary sense. The selective advantage of correlating content-contingent stimuli reflects the putative common cause of temporally or spatially contiguous inputs. The selective consequences of such correlations are discussed by using examples from the evolution of signal form in sexual selection and model-mimic coevolution. We suggest that evolutionary justification might be considered in addition to neurophysiology plansibility when constructing representational models.