Natural decision theory: A general formalism for the analysis of evolved characteristics

Classical Decision Theory, a mature and highly developed theory of rational choice, can be applied within evolutionary biology to the question of what traits an organism ought “rationally” to adopt, given that it wants to maximize its fitness. In this way the powerful formalism of decision theory can be brought to bear on the problem of how to predict which characters will be favored by natural selection, or to explain why certain characters have been so favored.Under some circumstances the classical theory of decision can be applied as it stands to an evolutionary problem simply by substituting an appropriate measure of biological fitness for the decision-theoretic concept of “utility”. Under other circumstances, however, it is necessary to extend the classical rules of decision in certain new directions. The result is a family of decision calculi of which the classical is only one. The name “Natural Decision Theory” is proposed for this extended class of biologically relevant decision methods.The decision tree method of diagramming an evolutionary decision situation is illustrated for the classical and three non-classical decision criteria, and is suggested as a potential means of gaining new insights into evolutionary forces.     

Rationality Wars and the War on Terror: Explaining Terrorism and Social Unrest

Terrorism is problematic at multiple levels. Social scientists debate its cause; policymakers debate what to do about it; many debate the meaning and political use of the term; and many live in fear of it. Current explanations of terrorism hinge on competing models of decision making. Anthropologists are increasingly influential in decision theory as issues of rationality, culture, and evolutionary psychology are invoked to explain patterns in human decision making. In this article, I review and critique current explanations of terrorism, I relate these explanations to larger debates in decision theory and anthropology, and I present an example of how current schisms may be transcended.     

The economic approach to ‘theory of mind’

Theory of mind (ToM) is a great evolutionary achievement. It is a special intelligence that can assess not only one''s own desires and beliefs, but also those of others. Whether it is uniquely human or not is controversial, but it is clear that humans are, at least, significantly better at ToM than any other animal. Economists and game theorists have developed sophisticated and powerful models of ToM and we provide a detailed summary of this here. This economic ToM entails a hierarchy of beliefs. I know my preferences, and I have beliefs (a probabilistic distribution) about your preferences, beliefs about your beliefs about my preferences, and so on. We then contrast this economic ToM with the theoretical approaches of neuroscience and with empirical data in general. Although this economic view provides a benchmark and makes useful suggestions about empirical tendencies, it does not always generate a close fit with the data. This provides an opportunity for a synergistic interdisciplinary production of a falsifiable theory of bounded rationality. In particular, a ToM that is founded on evolutionary biology might well be sufficiently structured to have predictive power, while remaining quite general. We sketch two papers that represent preliminary steps in this direction.     

Human behavioral ecology and niche construction

We examine the relationship between niche construction theory (NCT) and human behavioral ecology (HBE), two branches of evolutionary science that are important sources of theory in archeology. We distinguish between formal models of niche construction as an evolutionary process, and uses of niche construction to refer to a kind of human behavior. Formal models from NCT examine how environmental modification can change the selection pressures that organisms face. In contrast, formal models from HBE predict behavior assuming people behave adaptively in their local setting, and can be used to predict when and why people engage in niche construction. We emphasize that HBE as a field is much broader than foraging theory and can incorporate social and cultural influences on decision‐making. We demonstrate how these approaches can be formally incorporated in a multi‐inheritance framework for evolutionary research, and argue that archeologists can best contribute to evolutionary theory by building and testing models that flexibly incorporate HBE and NCT elements.     

Classical conditioning,signal detection,and evolution

Strength of classical conditioning is increased either by increasing discriminability of the conditioned stimulus (CS) from the background, or by increasing contingency between conditioned and unconditioned stimili (US).Classical conditioning can be regarded as a decision process in which the subject has to decide whether or not to respond with a conditioned response in the presence or absence of the CS. According to modern evolutionary theories, it might be assumed that this decision process maximizes the trade-off between cost and benefits.By assuming that the decision rule maximizes expected benefit, the empirical relationship between contingency and the strength of classical conditioning is theoretically derived. In addition, when the decision rule is incorporated to a signal detection paradigm, theoretical results describing the relationship between CS discriminability and CS – US contingency with the strength of classical conditioning are in agreement with experimental data.     

The equivalence of neo-Darwinism and Walrasian equilibrium: in defense of <Emphasis Type="Italic">Organismus economicus</Emphasis>

Neo-Darwinism is based on the same principles as the Walrasian analysis of equilibrium. This may be surprising for evolutionary economists who resort to neo-Darwinism as a result of their dissatisfaction with Walrasian economics. As it is well-known, the principle of rationality does not play a role in neo-Darwinism. In fact, the whole (neo-)Darwinian agenda became popular exactly because it expunged the idea of rationality from nature, and hence, from equilibrium. It is less known, however, that the rationality principle is also not central in Walrasian equilibrium analysis. Therefore, if we find that the rationality principle must be central to the analysis of decision making of human and nonhuman organisms, we must advance organomics. Organomics is bioeconomics understood as the use of rational choice to the study of the behavior of human and nonhuman organisms. Organomics offers a different starting point than the one offered by neo-Darwinism.     

Beyond the DP/DSS controversy

Paul Turke's “Which humans behave adaptively, and why does it matter?” shows, if he we are to take him as being representative of “Darwinian social science” in general, that his school of thought has moved surprisingly close to that of its “Darwinian psychology” critics in accepting the importance if not the primacy of the psychological level of explanation in applying evolutionary theory to human behavior. Disagreements continue over whether the adaptiveness of current behavior should be viewed as an occasionally interesting question because of the light it can shed on evolved psychological mechanisms, or whether, as Turke maintains, it is the central question for human sociobiology. In any event, the “vertically integrated approach,” utterly ignored by Turke, incorporates Darwinian Psychology and is far more powerful than is Turke's approach in explicating the relationship between genes and culture, thereby rendering the current debate pointless.     

What is optimal about motor control?

This article poses a controversial question: is optimal control theory useful for understanding motor behavior or is it a misdirection? This question is becoming acute as people start to conflate internal models in motor control and perception (Poeppel et?al., 2008; Hickok et?al., 2011). However, the forward models in motor control are not the generative models used in perceptual inference. This Perspective tries to highlight the differences between internal models in motor control and perception and asks whether optimal control is the right way to think about things. The issues considered here may have broader implications for optimal decision theory and Bayesian approaches to learning and behavior in general.     

Empirical Complexities in the Genetic Foundations of Lethal Mutagenesis

From population genetics theory, elevating the mutation rate of a large population should progressively reduce average fitness. If the fitness decline is large enough, the population will go extinct in a process known as lethal mutagenesis. Lethal mutagenesis has been endorsed in the virology literature as a promising approach to viral treatment, and several in vitro studies have forced viral extinction with high doses of mutagenic drugs. Yet only one empirical study has tested the genetic models underlying lethal mutagenesis, and the theory failed on even a qualitative level. Here we provide a new level of analysis of lethal mutagenesis by developing and evaluating models specifically tailored to empirical systems that may be used to test the theory. We first quantify a bias in the estimation of a critical parameter and consider whether that bias underlies the previously observed lack of concordance between theory and experiment. We then consider a seemingly ideal protocol that avoids this bias—mutagenesis of virions—but find that it is hampered by other problems. Finally, results that reveal difficulties in the mere interpretation of mutations assayed from double-strand genomes are derived. Our analyses expose unanticipated complexities in testing the theory. Nevertheless, the previous failure of the theory to predict experimental outcomes appears to reside in evolutionary mechanisms neglected by the theory (e.g., beneficial mutations) rather than from a mismatch between the empirical setup and model assumptions. This interpretation raises the specter that naive attempts at lethal mutagenesis may augment adaptation rather than retard it.     

Cooperation and Stability through Periodic Impulses

Basic games, where each individual chooses between two strategies, illustrate several issues that immediately emerge from the standard approach that applies strategic reasoning, based on rational decisions, to predict population behavior where no rationality is assumed. These include how mutual cooperation (which corresponds to the best outcome from the population perspective) can evolve when the only individually rational choice is to defect, illustrated by the Prisoner''s Dilemma (PD) game, and how individuals can randomize between two strategies when neither is individually rational, illustrated by the Battle of the Sexes (BS) game that models male-female conflict over parental investment in offspring. We examine these questions from an evolutionary perspective where the evolutionary dynamics includes an impulsive effect that models sudden changes in collective population behavior. For the PD game, we show analytically that cooperation can either coexist with defection or completely take over the population, depending on the strength of the impulse. By extending these results for the PD game, we also show that males and females each evolve to a single strategy in the BS game when the impulsive effect is strong and that weak impulses stabilize the randomized strategies of this game.     

Modeling social and evolutionary games

When game theory was introduced to biology, the components of classic game theory models were replaced with elements more befitting evolutionary phenomena. The actions of intelligent agents are replaced by phenotypic traits; utility is replaced by fitness; rational deliberation is replaced by natural selection. In this paper, I argue that this classic conception of comprehensive reapplication is misleading, for it overemphasizes the discontinuity between human behavior and evolved traits. Explicitly considering the representational roles of evolutionary game theory brings to attention areas of overlap that are often neglected, and so a range of evolutionary possibilities that are often overlooked. The clarifications this analysis provides are well illustrated by-and particularly valuable for-game theoretic treatments of the evolution of social behavior.     

Behavioural social choice: a status report

Behavioural social choice has been proposed as a social choice parallel to seminal developments in other decision sciences, such as behavioural decision theory, behavioural economics, behavioural finance and behavioural game theory. Behavioural paradigms compare how rational actors should make certain types of decisions with how real decision makers behave empirically. We highlight that important theoretical predictions in social choice theory change dramatically under even minute violations of standard assumptions. Empirical data violate those critical assumptions. We argue that the nature of preference distributions in electorates is ultimately an empirical question, which social choice theory has often neglected. We also emphasize important insights for research on decision making by individuals. When researchers aggregate individual choice behaviour in laboratory experiments to report summary statistics, they are implicitly applying social choice rules. Thus, they should be aware of the potential for aggregation paradoxes. We hypothesize that such problems may substantially mar the conclusions of a number of (sometimes seminal) papers in behavioural decision research.     

Network design meets in silico evolutionary biology

Cell fate is programmed through gene regulatory networks that perform several calculations to take the appropriate decision. In silico evolutionary optimization mimics the way Nature has designed such gene regulatory networks. In this review we discuss the basic principles of these evolutionary approaches and how they can be applied to engineer synthetic networks. We summarize the basic guidelines to implement an in silico evolutionary design method, the operators for mutation and selection that iteratively drive the network architecture towards a specified dynamical behavior. Interestingly, as it happens in natural evolution, we show the existence of patterns of punctuated evolution. In addition, we highlight several examples of models that have been designed using automated procedures, together with different objective functions to select for the proper behavior. Finally, we briefly discuss the modular designability of gene regulatory networks and its potential application in biotechnology.     

WHAT DOES RESPECT FOR THE PATIENT'S AUTONOMY REQUIRE?

Personal autonomy presupposes the notion of rationality. What is not so clear is whether, and how, a compromise of rationality to various degrees will diminish a person's autonomy. In bioethical literature, three major types of threat to the rationality of a patient's medical decision are identified: insufficient information, irrational beliefs/desires, and influence of different framing effects. To overcome the first problem, it is suggested that patients be provided with information about their diseases and treatment choices according to the objective standard. I shall explain how this should be finessed. Regarding the negative impact of irrational beliefs/desires, some philosophers have argued that holding irrational beliefs can still be an expression of autonomy. I reject this argument because the degree of autonomy of a decision depends on the degree of rationality of the beliefs or desires on which the decision is based. Hence, to promote patient autonomy, we need to eliminate irrational beliefs by the provision of evidence and good arguments. Finally, I argue that the way to smooth out the framing effects is to present the same information in different perspectives: it is too often assumed that medical information can always be given in a complete and unadorned manner. This article concludes with a cautionary note that the protection of patient autonomy requires much more time and effort than the current practice usually allows.     

Expected utility violations evolve under status-based selection mechanisms

The expected utility theory of decision making under uncertainty, a cornerstone of modern economics, assumes that humans linearly weight “utilities” for different possible outcomes by the probabilities with which these outcomes occur. Despite the theory's intuitive appeal, both from normative and from evolutionary perspectives, many experiments demonstrate systematic, though poorly understood, patterns of deviation from EU predictions. This paper offers a novel theoretical account of such patterns of deviation by demonstrating that EU violations can emerge from evolutionary selection when individual “status” affects inclusive fitness. In humans, battles for resources and social standing involve high-stakes decision making, and assortative mating ensures that status matters for fitness outcomes. The paper therefore proposes grounding the study of decision making under uncertainty in an evolutionary game-theoretic framework.     

Evolution to alternative levels of stable diversity leaves areas of niche space unexplored

One of the oldest and most persistent questions in ecology and evolution is whether natural communities tend to evolve toward saturation and maximal diversity. Robert MacArthur’s classical theory of niche packing and the theory of adaptive radiations both imply that populations will diversify and fully partition any available niche space. However, the saturation of natural populations is still very much an open area of debate and investigation. Additionally, recent evolutionary theory suggests the existence of alternative evolutionary stable states (ESSs), which implies that some stable communities may not be fully saturated. Using models with classical Lotka-Volterra ecological dynamics and three formulations of evolutionary dynamics (a model using adaptive dynamics, an individual-based model, and a partial differential equation model), we show that following an adaptive radiation, communities can often get stuck in low diversity states when limited by mutations of small phenotypic effect. These low diversity metastable states can also be maintained by limited resources and finite population sizes. When small mutations and finite populations are considered together, it is clear that despite the presence of higher-diversity stable states, natural populations are likely not fully saturating their environment and leaving potential niche space unfilled. Additionally, within-species variation can further reduce community diversity from levels predicted by models that assume species-level homogeneity.     

Evolutionary stability and quasi-stationary strategy in stochastic evolutionary game dynamics

Stochastic evolutionary game dynamics for finite populations has recently been widely explored in the study of evolutionary game theory. It is known from the work of Traulsen et al. [2005. Phys. Rev. Lett. 95, 238701] that the stochastic evolutionary dynamics approaches the deterministic replicator dynamics in the limit of large population size. However, sometimes the limiting behavior predicted by the stochastic evolutionary dynamics is not quite in agreement with the steady-state behavior of the replicator dynamics. This paradox inspired us to give reasonable explanations of the traditional concept of evolutionarily stable strategy (ESS) in the context of finite populations. A quasi-stationary analysis of the stochastic evolutionary game dynamics is put forward in this study and we present a new concept of quasi-stationary strategy (QSS) for large but finite populations. It is shown that the consistency between the QSS and the ESS implies that the long-term behavior of the replicator dynamics can be predicted by the quasi-stationary behavior of the stochastic dynamics. We relate the paradox to the time scales and find that the contradiction occurs only when the fixation time scale is much longer than the quasi-stationary time scale. Our work may shed light on understanding the relationship between the deterministic and stochastic methods of modeling evolutionary game dynamics.     

The evolution of theory of mind on welfare tradeoff ratios

People seem to attribute beliefs and desires to another person when interacting with them. Such a “theory of mind” capacity is essential for complex and uniquely human behavior such as language, but its evolutionary origin remains elusive. Using the formal tools of evolutionary game theory, we asked what environmental properties are necessary to select for a basic form of theory of mind—the ability to infer the prosociality, quantified by the welfare tradeoff ratio, of another person toward oneself. We found that none of the environments studied in classical or evolutionary game theory give an advantage to this form of theory of mind capacities; theory of mind is advantageous only in a new class of environments with stable opponents and variable payoff structures. In two behavioral experiments (n = 91) we verified that people can, and do use theory of mind in such an environment. These results suggest that some features of early humans’ social environment that were previously neglected in evolutionary game theory may be responsible for the evolution of people’s complex social capacities.     

Dynamic decision-making in uncertain environments II. Allais paradox in human behavior

In both animal and human behavioral repertoires, classical expected utility theory is considered a fundamental element of decision making under conditions of uncertainty. This theory has been widely applied to problems of animal behavior and evolutionary game theory, as well as to human economic behavior. The Allais paradox hinges on the expression of avoidance of bankruptcy by humans, or death by starvation in animals. This paradox reveals that human behavioral patterns are often inconsistent with predictions under the classical expected utility theory as formulated by von Neumann and Morgenstern. None of the many attempts to reformulate utility theory has been entirely successful in resolving this paradox with rigorous logic. We present a simple, but novel approach to the theory of decision making, in which utility is dependent on current wealth, and in which losses are more heavily weighted than gains. Our approach resolves the Allais paradox in a manner that is consistent with how humans formulate decisions under uncertainty. Our results indicate that animals, including humans, are in principle risk-averse. Our restructuring of dynamic utility theory presents a basic optimization scheme for sequential or dynamic decisions in both animals and humans.     

The Impact of Menstrual Cycle Phase on Economic Choice and Rationality

It is well known that hormones affect both brain and behavior, but less is known about the extent to which hormones affect economic decision-making. Numerous studies demonstrate gender differences in attitudes to risk and loss in financial decision-making, often finding that women are more loss and risk averse than men. It is unclear what drives these effects and whether cyclically varying hormonal differences between men and women contribute to differences in economic preferences. We focus here on how economic rationality and preferences change as a function of menstrual cycle phase in women. We tested adherence to the Generalized Axiom of Revealed Preference (GARP), the standard test of economic rationality. If choices satisfy GARP then there exists a well-behaved utility function that the subject’s decisions maximize. We also examined whether risk attitudes and loss aversion change as a function of cycle phase. We found that, despite large fluctuations in hormone levels, women are as technically rational in their choice behavior as their male counterparts at all phases of the menstrual cycle. However, women are more likely to choose risky options that can lead to potential losses while ovulating; during ovulation women are less loss averse than men and therefore more economically rational than men in this regard. These findings may have market-level implications: ovulating women more effectively maximize expected value than do other groups.