Abstract

The Bass diffusion equation is a well-known and established modeling approach for describing new product adoption in a competitive market. This model also describes diffusion phenomena in various contexts: infectious disease spread modeling and estimation, rumor spread on social networks, prediction of renewable energy technology markets, among others. Most of these models, however, consider a deterministic trajectory of the associated state variable (e.g., market-share). In reality, the diffusion process is subject to noise, and a stochastic component must be added to the state dynamics. The stochastic Bass model has also been studied in many areas, such as energy markets and marketing. Exploring the stochastic version of the Bass diffusion model, we propose in this work an approximation of (stochastic) optimal control surfaces for a continuous-time problem arising from a 2 × 2 skew symmetric evolutionary game, providing the stochastic counterpart of the Fourier-based optimal control approximation already existent in the literature.

Meeting Name

IISE Annual Conference & Expo 2023

Department(s)

Engineering Management and Systems Engineering

Keywords and Phrases

Optimal􀀁control,􀀁Fourier􀀁approximation, evolutionary game, learning, stochastic Bass model.

Document Type

Article - Conference proceedings

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2024 ProQuest LLC, All Rights Reserved

Publication Date

2023

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