arXiv
Open Access
2016
Variational Inference with Agent-Based Models
Wen Dong
Abstrak
In this paper, we develop a variational method to track and make predictions about a real-world system from continuous imperfect observations about this system, using an agent-based model that describes the system dynamics. By combining the power of big data with the power of model-thinking in the stochastic process framework, we can make many valuable predictions. We show how to track the spread of an epidemic at the individual level and how to make short-term predictions about traffic congestion. This method points to a new way to bring together modelers and data miners by turning the real world into a living lab.
Topik & Kata Kunci
Penulis (1)
W
Wen Dong
Akses Cepat
Informasi Jurnal
- Tahun Terbit
- 2016
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓