:3917 server; the fourth, peek, is the analytic answer-key read that powers
evaluation.
observe
The full ECS state, read out exactly without stepping — facts, not pixels.
POST /observe →
a flat table of entities and components.peek
The exact probability distribution over the next step’s outcome, read analytically from the
declared generative model — not sampled. The answer key.
step
Advance one tick deterministically, sampling from exactly the distribution
peek reported.
POST /step.fork
Clone the world mid-episode and branch a counterfactual (the do-operator) — change one
action, the rest stays bit-identical.
POST /fork. See Forks.observe — exact current state
POST /observe returns every entity as a flattened, machine-readable projection (RichEntityData),
addressable by id. No interpretation, no pixels — the world as a table. It
does not advance time.
step — deterministic advance
POST /step runs the shared schedule N ticks. Given the same seed and inputs, the trajectory is
bit-identical. Stepping consumes the world’s single sanctioned RNG stream.
fork — counterfactual branching
POST /fork deep-clones the world into an isolated branch; you apply an intervention and step the fork
without touching the main world. The same systems run on the fork, so a counterfactual is a true
do-operator, not an approximation. Full guide →
peek — the exact next-step distribution
peek is what makes Euca an answer key: it reads the true distribution over the next step’s
declared stochastic outcomes — as a distribution, not a sample — directly from the generative
rules. Only a white-box, executable world can report its own exact next-step
odds, because the randomness is declared in the code. peek is first-class in the euca-online
world engine and is surfaced through the truth-hiding evaluation boundary
(it is deliberately not a plain :3917 route — a contestant must never see the truth during a
scored run).
The soundness invariant:
peek == step. A named test holds the distribution peek reports to be
byte-for-byte the one step samples from. No rounding, no approximation. This is why a perfect
predictor scores exactly 0 nats of regret, and why counterfactual
predictions can be graded against forked exact distributions.Scope — what’s exact, and what isn’t
The exact distribution covers the declared discrete/categorical layer — a rule fires or not, a branch outcome. Continuous physics evolves deterministically (a point next-state, not a distribution). So “exact distribution” means the declared variables’ true odds, not a full predictive density over every position and velocity. See Determinism for the reproducibility guarantee and Evaluation for how this becomes a score.The four verbs in action
A runnable walkthrough: observe a world, fork it, intervene, and compare.