Abstract
From neurons to insects to societies, across biology we see impressive feats of collective information processing. What strategies do these systems use to perform useful computations? Moving toward an answer to this question, this chapter focuses on common challenges in inferring models of complicated distributed systems and how the perspective of information theory and statistical physics is useful for understanding collective behavior.
| Original language | English (US) |
|---|---|
| Title of host publication | Advances in Info-Metrics |
| Subtitle of host publication | Information and Information Processing across Disciplines |
| Publisher | Oxford University Press |
| Pages | 81-112 |
| Number of pages | 32 |
| ISBN (Electronic) | 9780190636685 |
| DOIs | |
| State | Published - Jan 1 2020 |
Keywords
- Collective behavior
- Collective computation
- Dimensionality reduction
- Maximum entropy models
- Model inference
- Model reduction
- Phase transitions
- Sloppy models
- Systems biology
ASJC Scopus subject areas
- Economics, Econometrics and Finance(all)
- General Business, Management and Accounting