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T4 (MarginFactor): scored outcomes via Gaussian-margin EP evidence

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Adds soft Gaussian-observation evidence on the per-pair diff variable,
enabling continuous score margins as a richer alternative to ranks.

Public API:
- `Outcome::Scored([scores])` (non-breaking enum extension under
  `#[non_exhaustive]`).
- `Game::scored(teams, outcome, options)` constructor parallel to
  `Game::ranked`.
- `EventBuilder::scores([...])` fluent helper.
- `HistoryBuilder::score_sigma(σ)` knob (default 1.0, validated > 0).
- `GameOptions::score_sigma`.
- `EventKind` re-exported from `lib.rs` (annotated `#[non_exhaustive]`).
- New `InferenceError::InvalidParameter { name, value }` variant.

Internals:
- `MarginFactor` (`factor/margin.rs`): Gaussian observation factor that
  closes in one EP step; cavity-cached log-evidence mirrors `TruncFactor`.
- `BuiltinFactor::Margin` dispatch arm.
- `DiffFactor` enum in `game.rs` lets `Game::likelihoods` and the new
  `likelihoods_scored` share the per-pair link abstraction.
- Per-event `EventKind { Ranked, Scored { score_sigma } }` routed through
  `TimeSlice::add_events`, `iteration_direct`, and `log_evidence`.

Tests: 88 lib + 27 integration (4 new in `tests/scored.rs`); existing
goldens byte-identical.  Bench: `benches/scored.rs` baseline ~960µs for
60 events × 20-player pool with default convergence.

Plan: docs/superpowers/plans/2026-04-27-t4-margin-factor.md
Spec item marked Done.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
logaritmisk
2026-04-27 08:47:36 +02:00
co-authored by Claude Opus 4.7
parent 6bf3e7e294
commit 8b53cacd64
23 changed files with 3005 additions and 83 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/time_slice.rs
+59 -32
View File
@@ -44,6 +44,13 @@ impl Default for Skill {
}
}
#[derive(Debug, Clone, Copy)]
#[non_exhaustive]
pub enum EventKind {
Ranked,
Scored { score_sigma: f64 },
}
#[derive(Debug)]
struct Item {
agent: Index,
@@ -82,6 +89,7 @@ pub(crate) struct Event {
teams: Vec<Team>,
evidence: f64,
weights: Vec<Vec<f64>>,
kind: EventKind,
}
impl Event {
@@ -129,7 +137,14 @@ impl Event {
) {
let teams = self.within_priors(false, false, skills, agents);
let result = self.outputs();
let g = Game::ranked_with_arena(teams, &result, &self.weights, p_draw, arena);
let g = match self.kind {
EventKind::Ranked => {
Game::ranked_with_arena(teams, &result, &self.weights, p_draw, arena)
}
EventKind::Scored { score_sigma } => {
Game::scored_with_arena(teams, &result, &self.weights, score_sigma, arena)
}
};
for (t, team) in self.teams.iter_mut().enumerate() {
for (i, item) in team.items.iter_mut().enumerate() {
@@ -205,6 +220,7 @@ impl<T: Time> TimeSlice<T> {
composition: Vec<Vec<Vec<Index>>>,
results: Vec<Vec<f64>>,
weights: Vec<Vec<Vec<f64>>>,
kinds: Vec<EventKind>,
agents: &CompetitorStore<T, D>,
) {
let mut unique = Vec::with_capacity(10);
@@ -274,6 +290,7 @@ impl<T: Time> TimeSlice<T> {
teams,
evidence: 0.0,
weights,
kind: kinds[e],
}
});
@@ -299,13 +316,22 @@ impl<T: Time> TimeSlice<T> {
let teams = event.within_priors(false, false, &self.skills, agents);
let result = event.outputs();
let g = Game::ranked_with_arena(
teams,
&result,
&event.weights,
self.p_draw,
&mut self.arena,
);
let g = match event.kind {
EventKind::Ranked => Game::ranked_with_arena(
teams,
&result,
&event.weights,
self.p_draw,
&mut self.arena,
),
EventKind::Scored { score_sigma } => Game::scored_with_arena(
teams,
&result,
&event.weights,
score_sigma,
&mut self.arena,
),
};
for (t, team) in event.teams.iter_mut().enumerate() {
for (i, item) in team.items.iter_mut().enumerate() {
@@ -474,21 +500,28 @@ impl<T: Time> TimeSlice<T> {
// log_evidence is infrequent; a local arena avoids needing &mut self.
let mut arena = ScratchArena::new();
let run_event = |event: &Event, arena: &mut ScratchArena| -> f64 {
let teams = event.within_priors(online, forward, &self.skills, agents);
let result = event.outputs();
match event.kind {
EventKind::Ranked => {
Game::ranked_with_arena(teams, &result, &event.weights, self.p_draw, arena)
.evidence
.ln()
}
EventKind::Scored { score_sigma } => {
Game::scored_with_arena(teams, &result, &event.weights, score_sigma, arena)
.evidence
.ln()
}
}
};
if targets.is_empty() {
if online || forward {
self.events
.iter()
.map(|event| {
Game::ranked_with_arena(
event.within_priors(online, forward, &self.skills, agents),
&event.outputs(),
&event.weights,
self.p_draw,
&mut arena,
)
.evidence
.ln()
})
.map(|event| run_event(event, &mut arena))
.sum()
} else {
self.events.iter().map(|event| event.evidence.ln()).sum()
@@ -496,25 +529,14 @@ impl<T: Time> TimeSlice<T> {
} else if online || forward {
self.events
.iter()
.enumerate()
.filter(|(_, event)| {
.filter(|event| {
event
.teams
.iter()
.flat_map(|team| &team.items)
.any(|item| targets.contains(&item.agent))
})
.map(|(_, event)| {
Game::ranked_with_arena(
event.within_priors(online, forward, &self.skills, agents),
&event.outputs(),
&event.weights,
self.p_draw,
&mut arena,
)
.evidence
.ln()
})
.map(|event| run_event(event, &mut arena))
.sum()
} else {
self.events
@@ -609,6 +631,7 @@ mod tests {
],
vec![vec![1.0, 0.0], vec![0.0, 1.0], vec![1.0, 0.0]],
vec![],
vec![EventKind::Ranked; 3],
&agents,
);
@@ -685,6 +708,7 @@ mod tests {
],
vec![vec![1.0, 0.0], vec![0.0, 1.0], vec![1.0, 0.0]],
vec![],
vec![EventKind::Ranked; 3],
&agents,
);
@@ -764,6 +788,7 @@ mod tests {
],
vec![vec![1.0, 0.0], vec![0.0, 1.0], vec![1.0, 0.0]],
vec![],
vec![EventKind::Ranked; 3],
&agents,
);
@@ -795,6 +820,7 @@ mod tests {
],
vec![vec![1.0, 0.0], vec![0.0, 1.0], vec![1.0, 0.0]],
vec![],
vec![EventKind::Ranked; 3],
&agents,
);
@@ -860,6 +886,7 @@ mod tests {
],
vec![vec![1.0, 0.0], vec![1.0, 0.0], vec![1.0, 0.0]],
vec![],
vec![EventKind::Ranked; 3],
&agents,
);