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Single-leader-multiple-follower games with boundedly rational agents

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  • Tharakunnel, Kurian
  • Bhattacharyya, Siddhartha

Abstract

This paper studies a class of hierarchical games called single-leader-multiple-follower games (SLMFGs) that have important applications in economics and engineering. We consider such games in the context of boundedly rational agents that are limited in the information and computational power they may possess. Agents in our SLMFG are modeled as adaptive learners that use simple reinforcement learning schemes to learn their optimal behavior. The proposed learning approach is illustrated using a well-studied problem in economics. It is shown that with a patiently learning leader the repeated plays of the game result in approximate equilibrium outcomes.

Suggested Citation

  • Tharakunnel, Kurian & Bhattacharyya, Siddhartha, 2009. "Single-leader-multiple-follower games with boundedly rational agents," Journal of Economic Dynamics and Control, Elsevier, vol. 33(8), pages 1593-1603, August.
    • Handle: RePEc:eee:dyncon:v:33:y:2009:i:8:p:1593-1603
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    References listed on IDEAS

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    Cited by:

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    2. Guoling Wang & Miao Wang & Hui Yang & Guanghui Yang & Chun Wang, 2024. "Existence of $$\alpha $$ α -Robust Weak Nash Equilibria for Leader–Follower Population Games with Fuzzy Parameters," Journal of Optimization Theory and Applications, Springer, vol. 203(3), pages 2739-2758, December.
    3. Grigory Belyavsky & Natalya Danilova & Guennady Ougolnitsky, 2018. "A Markovian Mechanism of Proportional Resource Allocation in the Incentive Model as a Dynamic Stochastic Inverse Stackelberg Game," Mathematics, MDPI, vol. 6(8), pages 1-10, July.

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