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The Exploration-Exploitation Dilemma: A Multidisciplinary Framework

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  • Oded Berger-Tal
  • Jonathan Nathan
  • Ehud Meron
  • David Saltz

Abstract

The trade-off between the need to obtain new knowledge and the need to use that knowledge to improve performance is one of the most basic trade-offs in nature, and optimal performance usually requires some balance between exploratory and exploitative behaviors. Researchers in many disciplines have been searching for the optimal solution to this dilemma. Here we present a novel model in which the exploration strategy itself is dynamic and varies with time in order to optimize a definite goal, such as the acquisition of energy, money, or prestige. Our model produced four very distinct phases: Knowledge establishment, Knowledge accumulation, Knowledge maintenance, and Knowledge exploitation, giving rise to a multidisciplinary framework that applies equally to humans, animals, and organizations. The framework can be used to explain a multitude of phenomena in various disciplines, such as the movement of animals in novel landscapes, the most efficient resource allocation for a start-up company, or the effects of old age on knowledge acquisition in humans.

Suggested Citation

  • Oded Berger-Tal & Jonathan Nathan & Ehud Meron & David Saltz, 2014. "The Exploration-Exploitation Dilemma: A Multidisciplinary Framework," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-8, April.
    • Handle: RePEc:plo:pone00:0095693
    DOI: 10.1371/journal.pone.0095693
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    References listed on IDEAS

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    1. James G. March, 1991. "Exploration and Exploitation in Organizational Learning," Organization Science, INFORMS, vol. 2(1), pages 71-87, February.
    2. Nathaniel D. Daw & John P. O'Doherty & Peter Dayan & Ben Seymour & Raymond J. Dolan, 2006. "Cortical substrates for exploratory decisions in humans," Nature, Nature, vol. 441(7095), pages 876-879, June.
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    Cited by:

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    2. Dario Blanco-Fernandez & Stephan Leitner & Alexandra Rausch, 2022. "Interactions between the individual and the group level in organizations: The case of learning and autonomous group adaptation," Papers 2203.09162, arXiv.org.
    3. Leitner, Stephan & Wall, Friederike, 2022. "Micro-level dynamics in hidden action situations with limited information," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 372-393.
    4. Guo, Liying & Wang, Yang & Li, Meiling, 2024. "Exploration, exploitation and funding success: Evidence from junior scientists supported by the Chinese Young Scientists Fund," Journal of Informetrics, Elsevier, vol. 18(2).
    5. Krystyna Januszkiewicz & Natalia Paszkowska-Kaczmarek & Fekadu Aduna Duguma & Karol G. Kowalski, 2021. "Living in the “Age of Humans”. Envisioning CAD Architecture for the Challenges of the Anthropocene—Energy, Environment, and Well-Being," Energies, MDPI, vol. 14(19), pages 1-24, September.
    6. De Gennaro Aquino, Luca & Sornette, Didier & Strub, Moris S., 2023. "Portfolio selection with exploration of new investment assets," European Journal of Operational Research, Elsevier, vol. 310(2), pages 773-792.
    7. Noa Malem-Shinitski & Manfred Opper & Sebastian Reich & Lisa Schwetlick & Stefan A Seelig & Ralf Engbert, 2020. "A mathematical model of local and global attention in natural scene viewing," PLOS Computational Biology, Public Library of Science, vol. 16(12), pages 1-21, December.
    8. De Dreu, Carsten & Nijstad, Bernard A. & Baas, Matthijs, 2023. "Human Creativity: Functions, Mechanisms and Social Conditioning," OSF Preprints pz9yx, Center for Open Science.
    9. Serge Svizzero, 2016. "Foraging Wild Resources and Sustainable Economic Development," Post-Print hal-02146473, HAL.
    10. Péron, Guillaume, 2024. "Movement-based coexistence does not always require a functional trade-off," Ecological Modelling, Elsevier, vol. 487(C).

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