Exact solutions of the simplified March model for organizational learning
Creators
- 1. Department of Physics, The Catholic University of Korea, Bucheon 14662, Republic of Korea
Description
March's celebrated agent-based simulation model for organizational learning [J. G. March, Org. Sci. 2, 71 (1991)] has been extensively studied in recent decades. Yet the model has not been fully understood due to the lack of analytical solutions of the model. We simplify the March model to take an analytical approach using master equations. We then derive exact solutions for some of the simplest yet nontrivial cases, and perform numerical estimation of master equations for more complicated cases. Both analytical and numerical results are in good agreement with agent-based simulations. These results are also compared to those of the original March model. Our approach enables us to rigorously understand the results of the simplified model as well as the original model, to a large extent.
Files
10.1103_PhysRevE.110.014303.pdf
Files
(481.5 kB)
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Additional details
Identifiers
- DOI
- 10.1103/PhysRevE.110.014303;
- arXiv
- arXiv:2401.03640;
- Crossref Funder ID
- 10.13039/501100003725; 10.13039/501100014188;
Publishing Information
- Journal Title
- Physical Review E
- Journal Volume
- 110
- Journal Issue
- 1
- Journal Page Range
- 9 pgs.
- ISSN
- 1089-3787
INIS
- Country of Publication
- United States
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- Subject category
- S97: MATHEMATICAL METHODS AND COMPUTING;
- Descriptors DEI
- ANALYTICAL SOLUTION; COMPUTERIZED SIMULATION; DIFFERENTIAL EQUATIONS; E-LEARNING; EQUATIONS; EXACT SOLUTIONS; MATHEMATICAL MODELS; NEURAL NETWORKS; NONLINEAR PROGRAMMING; NUMERICAL SOLUTION; RIEMANN FUNCTION; SET THEORY; SIMULATION; STANDARDIZED TERMINOLOGY; SUPERCOMPUTERS; VECTOR PROCESSING
- Descriptors DEC
- CALCULATION METHODS; COMPUTERS; DIGITAL COMPUTERS; EDUCATION; EQUATIONS; FUNCTIONS; LEARNING; MATHEMATICAL SOLUTIONS; MATHEMATICS; PROGRAMMING; SIMULATION; TRAINING
Optional Information
- Contract/Grant/Project number
- 2022R1A2C1007358
- Notes
- Contact Email: Contact author: h2jo@catholic.ac.kr; Record automatically processed
- Funding organization
- National Research Foundation of Korea; Ministry of Science and ICT, South Korea