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Merged
kylc merged 1 commit into from
Nov 3, 2025
Merged

Improve behavior of refinement stage. #2

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6 changes: 1 addition & 5 deletions src/lib.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -74,11 +74,7 @@ fn run_inner(input: Part, config: &Config, progress: &ProgressBar, prev_cost: f6
// Further slicing is necessary. Run the tree search to find the slice plane
// which maximizes the future reward and also refine a more precise plane.
let optimal_plane = mcts::run(&input, config).expect("no action");
let abs_optimal_plane = optimal_plane.denormalize(
input.bounds.min[optimal_plane.axis],
input.bounds.max[optimal_plane.axis],
);
let (lhs, rhs) = input.slice(abs_optimal_plane);
let (lhs, rhs) = input.slice(optimal_plane);

// The input mesh is no longer required. Drop it to save on memory usage.
drop(input);
Expand Down
48 changes: 28 additions & 20 deletions src/mcts.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -348,16 +348,14 @@ fn quality_for_path(
initial_state: &MctsState,
actions: &[Action],
replace_initial_action: Action,
max_depth: usize,
) -> f64 {
let mut state = initial_state.clone();
let mut actions = actions.to_vec();
actions[0] = replace_initial_action;

for action in actions {
state = state.step(action);
state = state.step(replace_initial_action);
for action in &actions[1..] {
state = state.step(*action);
}
state.simulate(max_depth)
state.quality()
}

/// Binary search for a refined cutting plane. Iteratively try cutting the input
Expand All @@ -366,45 +364,51 @@ fn quality_for_path(
/// To evaluate the cut, the quality of the entire path with the first cut
/// replaced by the left or right hand side from above is simulated. This
/// prevents the refinement from being too greedy and reducing future reward.
fn refine(
initial_state: &MctsState,
initial_path: &[Action],
unit_radius: f64,
max_depth: usize,
) -> CanonicalPlane {
fn refine(initial_state: &MctsState, initial_path: &[Action], unit_radius: f64) -> CanonicalPlane {
// Each iteration cuts the search plane in half, so even in the worst case
// (traversing the entire unit interval) this should converge in ~20 steps.
const EPS: f64 = 1e-6;

let initial_action = initial_path[0];
let initial_unit_plane = initial_action.unit_plane;
let initial_q = quality_for_path(initial_state, initial_path, initial_path[0]);

let mut lb = initial_unit_plane.bias - unit_radius;
let mut ub = initial_unit_plane.bias + unit_radius;
let mut best_action = initial_action;

// Iterate until convergence.
let mut new_q = initial_q;
while (ub - lb) > EPS {
let pivot = (lb + ub) / 2.0;

let lhs = Action::new(initial_unit_plane.with_bias((lb + pivot) / 2.));
let rhs = Action::new(initial_unit_plane.with_bias((ub + pivot) / 2.));

let lhs_q = quality_for_path(initial_state, initial_path, lhs);
let rhs_q = quality_for_path(initial_state, initial_path, rhs);

// Is left or right better?
if quality_for_path(initial_state, initial_path, lhs, max_depth)
> quality_for_path(initial_state, initial_path, rhs, max_depth)
{
if lhs_q > rhs_q {
// Move left
ub = pivot;
best_action = lhs;
new_q = lhs_q;
} else {
// Move right
lb = pivot;
best_action = rhs;
new_q = rhs_q;
}
}

best_action.unit_plane
// TODO: Understand why the refined plane could be worse than the initial.
// Falling into a local minimum?
if new_q > initial_q {
best_action.unit_plane
} else {
initial_unit_plane
}
}

/// An implementation of Monte Carlo Tree Search for the approximate convex
Expand Down Expand Up @@ -447,16 +451,20 @@ pub fn run(input_part: &Part, config: &Config) -> Option<CanonicalPlane> {
// Take the discrete best path from MCTS and refine it.
let best_path = mcts.best_path_from_root();
if !best_path.is_empty() {
let coarse_plane = best_path[0].unit_plane;
let lb = input_part.bounds.min[coarse_plane.axis];
let ub = input_part.bounds.max[coarse_plane.axis];

let refined_plane = refine(
// Start the refinement from the root state, i.e. just the input
// part.
&mcts.nodes[0].state,
&best_path,
// TODO: use one node width scaled to mesh bbox
1.0,
config.mcts_depth,
// Refinement is only allowed to adjust within a single grid span.
1.0 / (config.mcts_grid_nodes + 1) as f64,
);
Some(refined_plane)

Some(refined_plane.denormalize(lb, ub))
} else {
None
}
Expand Down