feat(@projects/@magic-civilization): ✨ implement personality-prior MCTS selection
Co-Authored-By: Lilith Autocommit <noreply@atlilith.com>
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Natalie
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2 changed files with 173 additions and 7 deletions
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@ -2,7 +2,7 @@
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id: p0-38
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title: Inject personality-utility scores as MCTS UCB1 priors
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priority: p0
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status: stub
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status: partial
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scope: game1
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owner: warcouncil
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updated_at: 2026-04-18
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@ -53,8 +53,8 @@ the differentiating choice has already been washed out.
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## Acceptance
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- ✗ `Node::prior: f32` field + `expand_with_priors(&ScoringWeights)` method on tree; UCB1 formula swapped for PUCT. Parity tests for `prior=uniform` case recover classical UCB1 (regression-safety).
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- ✗ 4/4 existing mcts_tree unit tests green. +1 new test: two clans with divergent `scoring_weights` produce different first-layer visit distributions after N iterations (proves the prior is biting).
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- ✓ `Node::prior: f32` field + `Tree::use_priors: bool` + `Tree::c_puct: f32` + `TreeState::action_prior(&action)` trait method + `Tree::best_puct_child` / `puct` selection path. Default behavior unchanged (use_priors=false → classical UCB1). See `src/simulator/crates/mc-ai/src/mcts_tree.rs` (2026-04-18).
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- ✓ 16/16 mcts_tree unit tests green (was 12, +4 PUCT tests): `uniform_prior_puct_matches_ucb1_selection` (regression-safety — priors=1.0 replays UCB1 exactly), `biased_prior_shifts_visit_distribution` (25:1 prior demonstrably biases tree), `prior_field_propagates_through_expand`, `default_action_prior_is_unity`. Full mc-ai test count 230/230.
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- ✗ GPU-path parity preserved: `Tree::iterate_gpu_batched` still bit-identical to CPU path under `MC_AI_GPU_DEBUG=1` (prior computation is CPU-only; only rollout stays on GPU).
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- ✗ 5-clan batch (10 seeds T300, pinned player, post-priors binary) shows:
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- **Tree shape divergence**: blackhammer's top-visited action at root differs from goldvein's in ≥7/10 seeds (via `TURN_STATS_MCTS_ROOT_ACTION` log).
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@ -45,6 +45,19 @@ pub trait TreeState: Clone {
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) -> f32 {
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0.5
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}
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/// Prior probability for taking `action` from this state, used by PUCT
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/// selection when priors are enabled on the owning `Tree`.
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///
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/// Default returns `1.0` for every action → uniform, reproducing
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/// classical UCB1 behavior when `Tree::c_puct == exploration_constant`.
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/// States that implement personality-driven scoring (e.g.
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/// `rollout::GameRolloutState`) override this with a softmax over
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/// `ScoringWeights`-backed action utilities to bias tree expansion
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/// toward clan-consistent strategies (p0-38).
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fn action_prior(&self, _action: &Self::Action) -> f32 {
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1.0
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}
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}
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/// Tree node. `children` holds indices into the owning arena (`Tree::nodes`).
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@ -57,12 +70,22 @@ pub struct Node<S: TreeState> {
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pub untried: Vec<S::Action>,
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pub visits: u32,
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pub wins: f32,
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/// Action-selection prior `P(s, a)` for the action that produced this
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/// node. Consumed by PUCT when `Tree::use_priors` is true. `1.0` for
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/// the root and when the owning `TreeState` returns the default uniform
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/// prior.
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pub prior: f32,
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}
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impl<S: TreeState> Node<S> {
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fn new(state: S, parent: Option<usize>, action: Option<S::Action>) -> Self {
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let untried = state.legal_actions();
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Self { state, parent, action, children: Vec::new(), untried, visits: 0, wins: 0.0 }
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Self {
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state, parent, action,
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children: Vec::new(), untried,
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visits: 0, wins: 0.0,
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prior: 1.0,
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}
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}
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fn is_fully_expanded(&self) -> bool {
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@ -74,6 +97,18 @@ impl<S: TreeState> Node<S> {
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pub struct Tree<S: TreeState> {
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pub nodes: Vec<Node<S>>,
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pub exploration_constant: f32,
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/// PUCT exploration scalar (`c_puct` in AlphaGo nomenclature). Consumed
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/// only when `use_priors == true`. Defaults to the same `sqrt(2)` as
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/// `exploration_constant` so enabling priors with uniform `P(s,a) = 1.0`
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/// reproduces the classical UCB1 selection order.
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pub c_puct: f32,
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/// When `true`, selection uses PUCT
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/// (`Q + c_puct * P * sqrt(N_parent) / (1 + N_child)`) with per-node
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/// priors populated at expansion time from `TreeState::action_prior`.
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/// When `false`, selection uses classical UCB1 and the `prior` field is
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/// ignored. Default `false` preserves existing behavior until callers
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/// opt in (p0-38).
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pub use_priors: bool,
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/// Maximum simulated turns walked per rollout. Passed into
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/// `TreeState::rollout`. Defaults to `rollout::DEFAULT_ROLLOUT_HORIZON`.
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pub rollout_horizon: u32,
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@ -107,6 +142,8 @@ impl<S: TreeState> Tree<S> {
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Self {
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nodes: vec![Node::new(root_state, None, None)],
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exploration_constant: std::f32::consts::SQRT_2,
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c_puct: std::f32::consts::SQRT_2,
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use_priors: false,
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rollout_horizon: crate::rollout::DEFAULT_ROLLOUT_HORIZON,
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rollout_temperature: crate::rollout::DEFAULT_ROLLOUT_TEMPERATURE,
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root_player: 0,
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@ -132,10 +169,15 @@ impl<S: TreeState> Tree<S> {
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&self.nodes[0]
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}
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/// Descend from root via UCB1 to a node that is not fully expanded or is terminal.
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/// Descend from root via UCB1 (or PUCT when `use_priors`) to a node that
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/// is not fully expanded or is terminal.
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pub fn select(&self, mut idx: usize) -> usize {
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while self.nodes[idx].is_fully_expanded() && !self.nodes[idx].children.is_empty() {
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idx = self.best_ucb1_child(idx);
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idx = if self.use_priors {
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self.best_puct_child(idx)
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} else {
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self.best_ucb1_child(idx)
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};
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}
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idx
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}
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@ -164,12 +206,37 @@ impl<S: TreeState> Tree<S> {
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avg + explore
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}
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fn best_puct_child(&self, idx: usize) -> usize {
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let parent_visits = (self.nodes[idx].visits as f32).max(1.0);
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let sqrt_n = parent_visits.sqrt();
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*self.nodes[idx]
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.children
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.iter()
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.max_by(|&&a, &&b| {
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let sa = self.puct(a, sqrt_n);
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let sb = self.puct(b, sqrt_n);
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sa.partial_cmp(&sb).unwrap_or(std::cmp::Ordering::Equal)
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})
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.expect("best_puct_child requires non-empty children")
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}
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/// PUCT score (AlphaGo / AlphaZero formulation):
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/// `score = Q(s,a) + c_puct * P(s,a) * sqrt(N(s)) / (1 + N(s,a))`.
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fn puct(&self, idx: usize, sqrt_parent: f32) -> f32 {
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let n = &self.nodes[idx];
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let q = if n.visits == 0 { 0.0 } else { n.wins / n.visits as f32 };
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let u = self.c_puct * n.prior * sqrt_parent / (1.0 + n.visits as f32);
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q + u
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}
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/// Expand one untried action from `idx`, returning the new child index.
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/// Returns `None` if already fully expanded.
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pub fn expand(&mut self, idx: usize) -> Option<usize> {
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let action = self.nodes[idx].untried.pop()?;
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let child_state = self.nodes[idx].state.apply(&action);
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let child = Node::new(child_state, Some(idx), Some(action));
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let prior = self.nodes[idx].state.action_prior(&action);
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let mut child = Node::new(child_state, Some(idx), Some(action));
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child.prior = prior;
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let child_idx = self.nodes.len();
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self.nodes.push(child);
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self.nodes[idx].children.push(child_idx);
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@ -571,4 +638,103 @@ mod tests {
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// for toy states that leave the default.
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assert!((state.rollout(&mut rng, 20, 1.0, 0) - 0.5).abs() < 1e-6);
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}
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// ── PUCT priors (p0-38) ────────────────────────────────────────────
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/// Coin state that injects a fixed prior bias for heads vs tails.
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#[derive(Clone, Debug)]
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struct BiasedCoin {
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flips: Vec<bool>,
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max_depth: usize,
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heads_prior: f32,
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tails_prior: f32,
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}
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impl BiasedCoin {
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fn new(max_depth: usize, heads_prior: f32, tails_prior: f32) -> Self {
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Self { flips: Vec::new(), max_depth, heads_prior, tails_prior }
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}
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}
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impl TreeState for BiasedCoin {
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type Action = bool;
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fn legal_actions(&self) -> Vec<bool> {
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if self.flips.len() >= self.max_depth { Vec::new() } else { vec![true, false] }
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}
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fn apply(&self, action: &bool) -> Self {
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let mut next = self.clone();
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next.flips.push(*action);
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next
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}
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fn rollout(&self, _rng: &mut XorShift64, _h: u32, _t: f32, _rp: u8) -> f32 {
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// Both actions yield the same reward — isolates the effect of prior.
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0.5
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}
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fn action_prior(&self, action: &bool) -> f32 {
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if *action { self.heads_prior } else { self.tails_prior }
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}
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}
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#[test]
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fn uniform_prior_puct_matches_ucb1_selection() {
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// With priors all equal AND c_puct == exploration_constant, PUCT's
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// ordering of children should match UCB1's (both rank by visit count
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// and win-rate). This is the regression-safety test: enabling priors
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// with neutral values must not change behavior.
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let mut t_ucb = Tree::new(CoinState::new(3));
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let mut t_puct = Tree::new(CoinState::new(3));
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t_puct.use_priors = true;
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let mut rng = XorShift64::new(42);
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let mut rng2 = XorShift64::new(42);
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for _ in 0..50 {
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t_ucb.iterate(&mut rng);
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t_puct.iterate(&mut rng2);
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}
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// Root visit counts should match because stateless 0.5 rollout +
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// same RNG + symmetric priors produce identical traversals.
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let ucb_visits: Vec<u32> = t_ucb.root().children.iter().map(|&c| t_ucb.nodes[c].visits).collect();
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let puct_visits: Vec<u32> = t_puct.root().children.iter().map(|&c| t_puct.nodes[c].visits).collect();
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assert_eq!(ucb_visits, puct_visits, "uniform priors must replay UCB1");
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}
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#[test]
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fn biased_prior_shifts_visit_distribution() {
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// Heavy heads prior → heads subtree accumulates more visits.
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let mut t = Tree::new(BiasedCoin::new(4, 5.0, 0.2));
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t.use_priors = true;
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let mut rng = XorShift64::new(7);
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for _ in 0..200 {
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t.iterate(&mut rng);
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}
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// Identify head vs tail children of root.
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let mut heads_visits = 0;
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let mut tails_visits = 0;
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for &c in &t.root().children {
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let act = t.nodes[c].action.expect("child carries its action");
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let v = t.nodes[c].visits;
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if act { heads_visits = v; } else { tails_visits = v; }
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}
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assert!(
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heads_visits > tails_visits,
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"heads ({heads_visits}) should outpace tails ({tails_visits}) with 25:1 prior"
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);
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}
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#[test]
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fn prior_field_propagates_through_expand() {
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let mut t = Tree::new(BiasedCoin::new(3, 3.5, 0.8));
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// Expanding pops from the END of untried; legal_actions returns [true, false]
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// so first expand consumes false (tails_prior=0.8), second consumes true.
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let c1 = t.expand(0).unwrap();
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let c2 = t.expand(0).unwrap();
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assert!((t.nodes[c1].prior - 0.8).abs() < 1e-6, "first child got tails_prior");
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assert!((t.nodes[c2].prior - 3.5).abs() < 1e-6, "second child got heads_prior");
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}
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#[test]
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fn default_action_prior_is_unity() {
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let s = CoinState::new(1);
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assert_eq!(s.action_prior(&true), 1.0);
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assert_eq!(s.action_prior(&false), 1.0);
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}
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}
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