Extends ShipObservations beyond the old self+1-opponent layout to padded
teammate/opponent arrays (MAX_TEAMMATES=4, MAX_OPPONENTS=5, SIZE=83),
zero-filling slots past the real roster size the same way the old single-
opponent slot was zero-filled when absent.
Slot stability across ticks requires a persistent identity: Ship gains
spawn_index (set once by GameMode.spawn_ship, never reassigned — there's no
despawn path anywhere in this codebase, so a roster is fixed for the whole
episode/match). ai_ship_controller.gd's opponent discovery is rewritten from
"first non-self ship" to classify every other ship by team and sort by
spawn_index; training_mode.gd/ship_ai_controller.gd carry the equivalent
sorted lists through the training path so both agree on slot assignment for
the same roster.
training_mode.gd and match_mode.gd both gain a team_size export (default 1,
so every existing curriculum script and match keeps today's 1v1 behaviour
unchanged). This is plumbing only: no 2v2+ curriculum or reward design, and
no match-mode UI to pick team size, has been done yet. The two checkpoints
in Game/bots/promoted/ are fitted to the old 35-float layout and are not
migrated — expected to go stale until the next training run.
drag_coefficient/angular_drag/the idle angular-drag multiplier were applied
once per physics tick with no delta scaling, correct only because
project.godot never pins physics/common/physics_ticks_per_second and
Godot's default happens to be 60. _tick_scaled(k, state.step) makes the
decay rate invariant to tick rate instead. Also promotes the previously
hardcoded 0.9 idle angular-drag literal to an export, matching its sibling.
Three curriculum generations (2026-07-21 through 2026-08-04) all tried
gating *when* the policy could use vertical thrust/pitch-roll on top of a
continuous Gaussian action space, and all three failed the same way: PPO's
action-distribution std collapsed within ~10% of steps and never recovered,
landing at a 15-32% win rate vs the grounded reference regardless of
mechanism (hard mask, then a gradual ramp). Generation 3's final attempt
just landed at 24% — the worst of the three.
Root cause, verified against this project's own physics: hovering this ship
requires *holding* thrust.y ~= 0.408 continuously (mass 5.0, vertical_thrust
120, gravity 9.8). A collapsed near-zero-mean Gaussian can brush that value
but never sustain it long enough to earn the reward gradient that would
move the mean — no amount of gating *when* the axis acts fixes a problem in
*how* the policy represents a decision on it. This also independently found
and fixes a real bug: godot_rl never marks an episode timeout as a
truncation, so PPO was bootstrapping V(s)=0 on every 30s draw in every
generation to date.
- Game/scripts/ship_action_codec.gd (new): single source of truth for a
per-axis MultiDiscrete action space (7 heads, nvec [5,5,5,5,5,5,2]) shared
by training and in-game inference, replacing the continuous Gaussian.
thrust_y's bins are deliberately asymmetric so a random policy drifts
through the volume instead of floor-pinning. Legacy continuous decode
(ai_ship_controller.gd's old logic) preserved verbatim so every
pre-generation-4 export (e.g. Game/bots/promoted/easy.json) keeps working
unchanged via an optional "action_space" JSON field.
- ship_observations.gd: append own contact state (SIZE 31 -> 35, append-only)
so the value function can see what wall_contact_penalty fires on.
- ship_ai_controller.gd: action space/decode via the codec; drop the
vertical_ramp/pitch_roll_ramp mechanism entirely; tilt_penalty default
lowered 4x (aerial approaches require pitching); flight telemetry
(airborne_fraction, mean_altitude, air_touch_fraction, vertical_thrust_mean)
and truncation-snapshot fields on get_info().
- training_mode.gd: new air_drill_chance state-setter branch (ball spawned
high, ships low, kept clear of walls) so aerial practice is forced by the
environment instead of relying on reward-driven exploration alone; snapshot
terminal observations before a timeout reset for the truncation fix.
- cosmic_env.py: remap ShipAIController's truncated/terminal_obs info into
SB3's TimeLimit.truncated/terminal_observation keys.
- train.py: --reset-logits (+ --reset-logits-heads) replaces the
now-meaningless --reset-std; new EntropyFloorCallback (a persistent
per-rollout ent_coef controller replacing the one-shot std-reset shock)
and per-head entropy logging; FlightTelemetryCallback; --air-drill-chance/
--tilt-penalty flags; optional AbortIfCallback kill-criterion.
- export_policy.py: writes the action_space block for MultiDiscrete models;
index-level parity check (argmax per head) instead of comparing floats.
- curriculum.py: full rewrite — 3 stages (bootstrap/selfplay/gauntlet), no
grounded stage, full action space live from step 1; deletes generation
1-3's checkpoint-lineage machinery (nothing to resume from); final report
evaluates against both promoted/easy.json and the new
promoted/reference-grounded.json (a copy of curric-s5-aggression, the
strongest grounded-era artifact, kept as a fixed yardstick).
- run_training.sh/.gitignore: commit only final.zip, not the ~2400
intermediate checkpoint files a single stage was writing (~500MB ->
~0.2MB per run); requirements.txt pinned (behaviour here now depends on
specific library internals, not just public APIs).
- test_action_space.py (new): offline rung-0 check catching a head-order
mismatch before it silently corrupts 24h of training.
Validated: GDScript compiles clean (Godot --headless --import + script
validation), free_play.tscn and training.tscn both boot headless without
errors, offline action-space assertions pass. Not yet run: the actual
smoke-training/A-B validation ladder steps in TRAINING.md's "Generation 4"
section, before committing to the full ~32h curriculum.
See TRAINING.md's "Generation 4" section for the full design writeup.
ship.gd's controllerless path and player_ship_controller.gd each
allocated a fresh ShipAction every physics tick; ai_ship_controller.gd
and rl_ship_controller.gd already avoid this via a persistent member.
Convert both to reuse a member instance, matching the existing
full-field-overwrite convention (rather than +=/-= off a fresh zero).
Also drop the completed items from TODO.md.
ship.gd, HUDController.gd, and goal.gd each declared their own TEAM_COLORS,
arena_boundary.gd/arena_deck.gdshader had a third pair, and HUD.tscn baked
in a fourth (hardcoded "BLUE"/"ORANGE" labels) — nose, goal rim, end zone,
and scoreboard all rendered different blues. New scripts/team_colors.gd
(class_name TeamColors) is now the single source every one of those reads
from, and team identity moves to purple/green.
Hull/Canopy/EngineGlowL/EngineGlowR are runtime-baked into one ArrayMesh
in _ready via SurfaceTool.append_from, dropping 4 MeshInstance3D children
to 1 (Nose/TailFin stay separate, they're retinted per-team). Skipped in
headless mode like the goal/arena_boundary visual builds, since physics
only cares about CollisionShape3D.
All 6 source surfaces (hull, canopy, engine_l x2, engine_r x2) carry
distinct materials, so this doesn't literally cut draw calls 6 to 3 as
TODO.md assumed — Godot still issues one draw call per surface regardless
of node count. The real win is scene-tree/transform overhead, not batching.
_apply_team_color() allocated a fresh StandardMaterial3D on every call, and
ran at least twice per ship (once from _ready at the default team, once from
the team setter when the game mode assigns the real team). Cache one
StandardMaterial3D per team in a static dict on Ship and reuse it across
every ship on that team.
Ship._emit_telemetry_data() ran get_euler()+trig every physics tick
for every ship regardless of whether a HUD was watching, wasting work
on AI ships and every headless training instance. Disable
_physics_process outright when headless, and skip emission the rest
of the time unless a signal actually has a listener.
Josh Creek