Evolutionarily stable learning schedules and cumulative culture in discrete generation models

被引:35
|
作者
Aoki, Kenichi [1 ]
Wakano, Joe Yuichiro [2 ]
Lehmann, Laurent [3 ]
机构
[1] Univ Tokyo, Dept Biol Sci, Bunkyo Ku, Tokyo 1130033, Japan
[2] Meiji Univ, Meiji Inst Adv Study Math Sci, Tama Ku, Kawasaki, Kanagawa 2148571, Japan
[3] UNIL Sorge, Dept Ecol & Evolut, CH-1015 Lausanne, Switzerland
关键词
Population genetics; Cumulative culture; Optimal strategy; TRANSMISSION; COEVOLUTION; INNOVATION; EMERGENCE; SELECTION; ONTOGENY; STRATEGY; AGE;
D O I
10.1016/j.tpb.2012.01.006
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Individual learning (e.g., trial-and-error) and social learning (e.g., imitation) are alternative ways of acquiring and expressing the appropriate phenotype in an environment. The optimal choice between using individual learning and/or social learning may be dictated by the life-stage or age of an organism. Of special interest is a learning schedule in which social learning precedes individual learning, because such a schedule is apparently a necessary condition for cumulative culture. Assuming two obligatory learning stages per discrete generation, we obtain the evolutionarily stable learning schedules for the three situations where the environment is constant, fluctuates between generations, or fluctuates within generations. During each learning stage, we assume that an organism may target the optimal phenotype in the current environment by individual learning, and/or the mature phenotype of the previous generation by oblique social learning. In the absence of exogenous costs to learning, the evolutionarily stable learning schedules are predicted to be either pure social learning followed by pure individual learning ("bang-bang" control) or pure individual learning at both stages ("flat" control). Moreover, we find for each situation that the evolutionarily stable learning schedule is also the one that optimizes the learned phenotype at equilibrium. (C) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码:300 / 309
页数:10
相关论文
共 50 条
  • [41] USE OF CUMULATIVE EFFICIENT SCORES FOR TESTING ORDERED-ALTERNATIVES IN DISCRETE MODELS
    HIROTSU, C
    BIOMETRIKA, 1982, 69 (03) : 567 - 577
  • [42] Deep learning optimal quantum annealing schedules for random Ising models
    Hegde, Pratibha Raghupati
    Passarelli, Gianluca
    Cantele, Giovanni
    Lucignano, Procolo
    NEW JOURNAL OF PHYSICS, 2023, 25 (07):
  • [43] EFFECTS OF VARYING FORCE PRODUCTION IN PRACTICE SCHEDULES OF CHILDREN LEARNING A DISCRETE MOTOR TASK
    PEASE, DG
    RUPNOW, AA
    PERCEPTUAL AND MOTOR SKILLS, 1983, 57 (01) : 275 - 282
  • [44] Enhancing discrete choice models with representation learning
    Sifringer, Brian
    Lurkin, Virginie
    Alahi, Alexandre
    TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2020, 140 (140) : 236 - 261
  • [45] SOME CURRENT PROBLEMS IN DISCRETE MODELS OF LEARNING
    RESTLE, F
    IEEE TRANSACTIONS ON APPLICATIONS AND INDUSTRY, 1964, 83 (74): : 277 - &
  • [46] Online learning in discrete hidden Markov models
    Alamino, Roberto
    Caticha, Nestor
    BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING, 2006, 872 : 187 - +
  • [47] Learning of Discrete Graphical Models with Neural Networks
    Abhijith, J.
    Lokhov, Andrey Y.
    Misra, Sidhant
    Vuffray, Marc
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 33, NEURIPS 2020, 2020, 33
  • [48] Active Learning for Discrete Latent Variable Models
    Jha, Aditi
    Ashwood, Zoe C.
    Pillow, Jonathan W.
    NEURAL COMPUTATION, 2024, 36 (03) : 437 - 474
  • [49] Variational Formulation of Stable Discrete k.p Models
    Frensley, William R.
    18TH INTERNATIONAL WORKSHOP ON COMPUTATIONAL ELECTRONICS (IWCE 2015), 2015,
  • [50] Evolution of social learning does not explain the origin of human cumulative culture
    Enquist, Magnus
    Ghirlanda, Stefano
    JOURNAL OF THEORETICAL BIOLOGY, 2007, 246 (01) : 129 - 135