Many-agent interaction in the model of labour force training
Irina Zaitseva, Oleg Malafeyev, Sergei Strekopytov, Anna Ermakova,, Dmitry Shlaev
TL;DR
This paper develops continuous and discrete models for labour force training, utilizing differential game theory and dynamic programming to derive optimal training strategies.
Contribution
It introduces a novel application of differential games and dynamic programming to model and compute optimal labour force training strategies.
Findings
Optimal strategies can be calculated using the proposed models.
The models provide a framework for analyzing labour training dynamics.
Application of differential game theory enhances strategic decision-making in training.
Abstract
The continuous and discrete models of labour force training are being built. The application of the results from the theory of differential games and dynamic programming allows presenting the optimal strategies of labour force training that can be calculated.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsEducational Technology and Optimization · Engineering Education and Technology · Modeling, Simulation, and Optimization