A dynamic world changes continuously and so do its causal factors. Equities and bonds move in opposite directions for a decade, then fall together on a single afternoon. Steel deforms in proportion to load until it yields, and then it does not. An aircraft navigates one way in clean airflow and another way in a turbulence. The variables stayed the same, but governing regime changes, relations between them change and they change dynamically.
Causal reasoning asks what produces what, and what follows if you change something. Judea Pearl separated that into three levels: what you observe, what happens when you intervene, and what would have happened had the past gone differently.
In DeepCausality, the causal structure itself can also move. A system can add, retire, or rewire rules as it crosses from one regime into another, and time need not run in a straight line. That is what the project means by dynamic causality.
use deep_causality_core::CausalFlow;
// What happened: 10 mg is absorbed, then metabolized, and the patient responds.
let observed = CausalFlow::value(10.0)
.map(|dose| dose * 0.8) // absorption -> 8.0
.map(|level| level - 2.0) // metabolism -> 6.0
.map(|level| level > 5.0) // response -> effective
.finish();
// What would have happened at a blood level of 3.0 instead.
let counterfactual = CausalFlow::value(10.0)
.map(|dose| dose * 0.8)
.alternate_value(3.0) // substitute mid-chain, and log the substitution
.map(|level| level - 2.0) // -> 1.0
.map(|level| level > 5.0) // -> ineffective
.finish();
assert_eq!(observed, Ok(true));
assert_eq!(counterfactual, Ok(false));Two runs, one chain. They differ by a single call. Both carry an audit log of every step and every substitution, so you can replay and inspect a conclusion long after the fact. The framework targets control systems in IoT, monitoring in cloud infrastructure, market models in finance, avionics, and scientific computing.
DeepCausality is a sandbox project at the LF AI & Data Foundation, part of the Linux Foundation. The Center for Dynamic Causality contributes research and offers commercial support for larger projects.
- Install and first model if you want code running in the next ten minutes.
- What dynamic causality is if you want the idea first.
- Worked examples in medicine, physics, aerospace, and mathematics.
- Discord and Discussions for questions. Newcomers are welcome; the concepts take a while to land, and asking is faster than reading.
