Fifty years of Theoretical Population Biology

Rosenberg, Noah A.

doi:10.1016/j.tpb.2020.04.001

Cited by 10 publications

(10 citation statements)

References 83 publications

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“…We were interested in more formally evaluating the influence that Orr's paper had on both theoretical and empirical research within the field. The influence of theoretical models on empirical research is often weak, or indirect (see Provine 1977; Fitzpatrick et al 2018; Rosenberg 2020). Theory papers on sexual selection and speciation, for example, are more often cited by other theory papers (∼56‐59% of the time) than by empirical papers (∼19‐23% of the time, with the remainder coming from reviews); these patterns do not align with the proportions of theory versus empirical papers in these disciplines (empirical papers represent the vast majority; see Fitzpatrick et al 2018).…”

Section: The Responsementioning

confidence: 99%

Allen Orr and the genetics of adaptation

Connallon

Hodgins

2021

Evolution

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Over most of the 20th century, evolutionary biologists predominantly subscribed to a strong form of "micro-mutationism," in which adaptive phenotypic divergence arises from allele frequency changes at many loci, each with a small effect on the phenotype. To be sure, there were well-known examples of large-effect alleles contributing to adaptation, yet such cases were generally regarded as atypical and unrepresentative of evolutionary change in general. In 1998, Allen Orr published a landmark theoretical paper in Evolution, which showed that both small-and large-effect mutations are likely to contribute to "adaptive walks" of a population to an optimum. Coupled with a growing set of empirical examples of large-effect alleles contributing to divergence (e.g., from QTL studies), Orr's paper provided a mathematical formalism that converted many evolutionary biologists from micro-mutationism to a more pluralistic perspective on the genetic basis of evolutionary change. We revisit the theoretical insights emerging from Orr's paper within the historical context leading up to 1998, and track the influence of this paper on the field of evolutionary biology through an examination of its citations over the last two decades and an analysis of the extensive body of theoretical and empirical research that Orr's pioneering paper inspired.

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Section: The Responsementioning

confidence: 99%

Allen Orr and the genetics of adaptation

Connallon

Hodgins

2021

Evolution

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“…Such a setting is, to some extent, analogous to the human decision in the context of the hybrid human-machine cooperation [65], a key research theme in the emerging interdisciplinary field of machine behaviour [66], in which humans can use algorithms to make decisions and subsequently the training of the same algorithms is affected by those decisions. The importance of environmental variations in population dynamics has long been recognized in theoretical ecology and population biology [24][25][26]. In a realistic social or ecological system, individual behaviours and environmental variations are inevitably coupled together [24,25].…”

Section: Discussionmentioning

confidence: 99%

“…Although the effect of environmental variations on population dynamics has long been recognized in theoretical ecology and population biology [24][25][26], it is only recently that there has been a surge of interest in constructing game-environment feedbacks [20,21,23,27,28] to understand the puzzle of cooperation, especially in structured populations [29][30][31]. Different from the conventional set-up in evolutionary game theory [8,9], the key conceptual innovation of these works is the introduction of multiple games [32,33], evolving games [34,35], dynamical system games [36] or stochastic games [37,38].…”

Section: Introductionmentioning

confidence: 99%

Learning enables adaptation in cooperation for multi-player stochastic games

Huang

Cao

Wang

2020

J. R. Soc. Interface.

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Interactions among individuals in natural populations often occur in a dynamically changing environment. Understanding the role of environmental variation in population dynamics has long been a central topic in theoretical ecology and population biology. However, the key question of how individuals, in the middle of challenging social dilemmas (e.g. the ‘tragedy of the commons’), modulate their behaviours to adapt to the fluctuation of the environment has not yet been addressed satisfactorily. Using evolutionary game theory, we develop a framework of stochastic games that incorporates the adaptive mechanism of reinforcement learning to investigate whether cooperative behaviours can evolve in the ever-changing group interaction environment. When the action choices of players are just slightly influenced by past reinforcements, we construct an analytical condition to determine whether cooperation can be favoured over defection. Intuitively, this condition reveals why and how the environment can mediate cooperative dilemmas. Under our model architecture, we also compare this learning mechanism with two non-learning decision rules, and we find that learning significantly improves the propensity for cooperation in weak social dilemmas, and, in sharp contrast, hinders cooperation in strong social dilemmas. Our results suggest that in complex social–ecological dilemmas, learning enables the adaptation of individuals to varying environments.

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“…Such a setup is, to some extent, analogous to the human decision in the context of the hybrid human-machine cooperation [64], a key research theme in the emerging interdisciplinary field -machine behavior [65], in which humans can use algorithms to make decisions and subsequently the training of the same algorithms is affected by those decisions. The importance of environmental variations in population dynamics has long been recognized in theoretical ecology and population biology [23,24,25]. In a realistic social or ecological system, individual behaviors and environmental variations are inevitably coupled together [23,24].…”

Section: Discussionmentioning

confidence: 99%

“…Although the effect of environmental variations on population dynamics has long been recognized in theoretical ecology and population biology [23,24,25], it is only recently that there has been a surge of interest in constructing game-environment feedbacks [19,20,22,26,27,28,29] to understand the puzzle of cooperation. Different from the conventional settings in evolutionary game theory [8,9], the key conceptual innovation of these work is the introduction of multiple games [30,31], evolving games [32], dynamical system games [33], or stochastic games [34,35].…”

Section: Introductionmentioning

confidence: 99%

Learning enables adaptation in cooperation for multi-player stochastic games

Huang,

Cao,

Wang

2020

Preprint

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Interactions among individuals in natural populations often occur in a dynamically changing environment. Understanding the role of environmental variation in population dynamics has long been a central topic in theoretical ecology and population biology. However, the key question of how individuals, in the middle of challenging social dilemmas (e.g., the "tragedy of the commons"), modulate their behaviors to adapt to the fluctuation of the environment has not yet been addressed satisfactorily. Utilizing evolutionary game theory and stochastic games, we develop a game-theoretical framework that incorporates the adaptive mechanism of reinforcement learning to investigate whether cooperative behaviors can evolve in the ever-changing group interaction environment. When the action choices of players are just slightly influenced by past reinforcements, we construct an analytical condition to determine whether cooperation can be favored over defection. Intuitively, this condition reveals why and how the environment can mediate cooperative dilemmas. Under our model architecture, we also compare this learning mechanism with two non-learning decision rules, and we find that learning significantly improves the propensity for cooperation in weak social dilemmas, and, in sharp contrast, hinders cooperation in strong social dilemmas. Our results suggest that in complex social-ecological dilemmas, learning enables the adaptation of individuals to varying environments.

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Fifty years of Theoretical Population Biology

Cited by 10 publications

References 83 publications

Allen Orr and the genetics of adaptation

Allen Orr and the genetics of adaptation

Learning enables adaptation in cooperation for multi-player stochastic games

Learning enables adaptation in cooperation for multi-player stochastic games

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