Hamilton’s rule, the evolution of behavior rules and the wizardry of control theory

Lehmann, Laurent

doi:10.1016/j.jtbi.2022.111282

Cited by 13 publications

(11 citation statements)

References 77 publications

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“…in the selection gradient (Appendix B.3.7; [97] for more details; also [41,92,97,98] for models with statemodulated local interactions). We only present results regarding directional selection of plastic traits here as disruptive selection for these traits has not yet been worked out, needing careful consideration of the nature of phenotypic deviation ( [153] for further discussion).…”

Section: Discussionmentioning

confidence: 99%

“…( 16) (e.g. behavioral response rules, learning rules, neural networks [79,[84][85][86][87][88][89][90][91][92][93][94][95][96][97][98]). Some of these models conceive the evolving trait z itself as a function of age or state (e.g.…”

Section: Physiological Structurementioning

confidence: 99%

“…(eq. 19 in [98] for the more general case in group-structured population and Appendix B.3 here for derivation). The first two terms of eq.…”

Section: Physiological Structurementioning

confidence: 99%

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Evolutionary Game Theory and the Adaptive Dynamics Approach: Adaptation where Individuals Interact

Avila¹,

Mullon²

2023

Preprint

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Evolutionary game theory and the adaptive dynamics approach have made invaluable contributions to understand how gradual evolution leads to adaptation when individuals interact. Here, we review some of the basic tools that have come out of these contributions to model the evolution of quantitative traits in complex populations. We collect together mathematical expressions that describe directional and disruptive selection in class- and group-structured populations in terms of individual fitness, with the aims of bridging different models and interpreting selection. In particular, our review of disruptive selection suggests there are two main paths that can lead to diversity: (i) when individual fitness increases more than linearly with trait expression; (ii) when trait expression simultaneously increases the probability that an individual is in a certain context (e.g. a given age, sex, habitat, size or social environment) and fitness in that context. We provide various examples of these and more broadly argue that population structure lays the ground for the emergence of polymorphism with unique characteristics. Beyond this, we hope that the descriptions of selection we present here help see the tight links among fundamental branches of evolutionary biology, from life-history to social evolution through evolutionary ecology, and thus favour further their integration.

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Section: Discussionmentioning

confidence: 99%

Section: Physiological Structurementioning

confidence: 99%

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Evolutionary Game Theory and the Adaptive Dynamics Approach: Adaptation where Individuals Interact

Avila¹,

Mullon²

2023

Preprint

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show abstract

“…A wide range of models in behavioural ecology and life-history theory can be captured conceptually by equation (3.9) (e.g. behavioural response rules, learning rules, neural networks [81][82][83]89,[94][95][96][97][98][99][100][101][102][103][104][105]). Some of these models conceive the evolving trait z itself as a function of age or state (e.g.…”

Section: (A) Matrix Population Modelsmentioning

confidence: 99%

“…when growing larger others might respond by growing even larger). This ‘anticipation’ is taken into account in the term ∂v~∘false(afalse)/false(∂x∘false(afalse)false) in the selection gradient (electronic supplementary material, appendix B.3.7; [81] for more details; also [41,81–83] for models with state-modulated local interactions). We only present results regarding directional selection of plastic traits here as disruptive selection for these traits has not yet been worked out, needing careful consideration of the nature of phenotypic deviation ([78] for further discussion).…”

Section: Class-structured Populations: Reproductive Values As the Exc...mentioning

confidence: 99%

Evolutionary game theory and the adaptive dynamics approach: adaptation where individuals interact

Avila

Mullon

2023

Phil. Trans. R. Soc. B

View full text Add to dashboard Cite

Evolutionary game theory and the adaptive dynamics approach have made invaluable contributions to understanding how gradual evolution leads to adaptation when individuals interact. Here, we review some of the basic tools that have come out of these contributions to model the evolution of quantitative traits in complex populations. We collect together mathematical expressions that describe directional and disruptive selection in class- and group-structured populations in terms of individual fitness, with the aims of bridging different models and interpreting selection. In particular, our review of disruptive selection suggests there are two main paths that can lead to diversity: (i) when individual fitness increases more than linearly with trait expression; (ii) when trait expression simultaneously increases the probability that an individual is in a certain context (e.g. a given age, sex, habitat, size or social environment) and fitness in that context. We provide various examples of these and more broadly argue that population structure lays the ground for the emergence of polymorphism with unique characteristics. Beyond this, we hope that the descriptions of selection we present here help see the tight links among fundamental branches of evolutionary biology, from life history to social evolution through evolutionary ecology, and thus favour further their integration. This article is part of the theme issue ‘Half a century of evolutionary games: a synthesis of theory, application and future directions’.

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Dead rats, dopamine, performance metrics, and peacock tails: Proxy failure is an inherent risk in goal-oriented systems

John¹,

Caldwell²,

McCoy³

et al. 2023

Behav Brain Sci

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When a measure becomes a target, it ceases to be a good measure. For example, when standardized test scores in education become targets, teachers may start ‘teaching to the test’, leading to breakdown of the relationship between the measure--test performance--and the underlying goal--quality education. Similar phenomena have been named and described across a broad range of contexts, such as economics, academia, machine-learning, and ecology. Yet it remains unclear whether these phenomena bear only superficial similarities, or if they derive from some fundamental unifying mechanism. Here, we propose such a unifying mechanism, which we label proxy failure. We first review illustrative examples and their labels, such as the ‘Cobra effect’, ‘Goodhart's law’, and ‘Campbell's law’. Second, we identify central prerequisites and constraints of proxy failure, noting that it is often only a partial failure or divergence. We argue that whenever incentivization or selection is based on an imperfect proxy measure of the underlying goal, a pressure arises which tends to make the proxy a worse approximation of the goal. Third, we develop this perspective for three concrete contexts, namely neuroscience, economics and ecology, highlighting similarities and differences. Fourth, we outline consequences of proxy failure, suggesting it is key to understanding the structure and evolution of goal-oriented systems. Our account draws on a broad range of disciplines, but we can only scratch the surface within each. We thus hope the present account elicits a collaborative enterprise, entailing both critical discussion as well as extensions in contexts we have missed.

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Hamilton’s rule, the evolution of behavior rules and the wizardry of control theory

Cited by 13 publications

References 77 publications

Evolutionary Game Theory and the Adaptive Dynamics Approach: Adaptation where Individuals Interact

Evolutionary Game Theory and the Adaptive Dynamics Approach: Adaptation where Individuals Interact

Evolutionary game theory and the adaptive dynamics approach: adaptation where individuals interact

Dead rats, dopamine, performance metrics, and peacock tails: Proxy failure is an inherent risk in goal-oriented systems

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