Datasets:
File size: 3,535 Bytes
7248ace | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 | from dataclasses import dataclass
import math
import numpy as np
HORIZON = 400
FRAMES_PER_STEP = 4
BRIGADE_LEFT = 10
BRIGADE_RIGHT = 40
BRIDGE_TOP = 32
GROUND = 37
@dataclass
class Bridge:
x: float
length: float
def overlaps_brigade(self) -> bool:
return self.x <= BRIGADE_RIGHT and self.x + self.length >= BRIGADE_LEFT
class BridgeCrossEnvironment:
score_cap = 500
def __init__(self, sticky_action_prob: float = 0.1, horizon: int = HORIZON):
self.sticky_action_prob = sticky_action_prob
self.horizon = min(horizon, HORIZON)
self.seed(0)
self.reset()
def seed(self, seed: int) -> None:
self.random = np.random.default_rng(seed)
def reset(self) -> None:
self.steps = self.score_timer = 0
self.spawn_timer = 0.0
self.multiplier = 1
self.y, self.vy = float(GROUND), 0.0
self.pressed = self.jumping = self.falling = self.on_bridge = self.terminal = False
self.bridges: list[Bridge] = []
@classmethod
def normalize_score(cls, score: float) -> float:
return min(max(score, 0), cls.score_cap) / cls.score_cap
def act(self, action: int) -> tuple[float, bool]:
if self.terminal:
return 0.0, True
pressed = self.pressed if self.random.random() < self.sticky_action_prob else action == 5
tap = pressed and not self.pressed
self.pressed = pressed
self.steps += 1
reward = 0
for frame in range(FRAMES_PER_STEP):
reward += self._advance_frame(tap and frame == 0)
if self.terminal:
break
self.terminal |= self.steps >= self.horizon
return float(reward), self.terminal
def _advance_frame(self, tap: bool) -> int:
if self.spawn_timer <= 0:
self.bridges.append(Bridge(153, self.random.uniform(20, 40)))
self.spawn_timer = self.random.uniform(50, 100)
self.spawn_timer -= 1
for bridge in self.bridges:
bridge.x -= 1
self.bridges = [bridge for bridge in self.bridges if bridge.x + bridge.length > 0]
above_bridge = any(bridge.overlaps_brigade() for bridge in self.bridges)
if self.y < 35 and not above_bridge:
self.falling, self.on_bridge = True, False
if self.jumping or self.falling:
self.y += self.vy
self.vy += 0.1 if self.pressed else 0.2
surface = BRIDGE_TOP if above_bridge else GROUND
if self.y > surface and self.vy > 0:
self.y, self.vy = float(surface), 0.0
self.jumping = self.falling = False
self.on_bridge = above_bridge
if tap and not self.jumping:
self.jumping, self.on_bridge = True, False
self.vy = -2
self.multiplier = math.ceil(self.multiplier / 2)
if not self.jumping and self.y > BRIDGE_TOP and above_bridge:
self.terminal = True
if self.on_bridge:
self.score_timer -= 1
if self.score_timer < 0:
reward = self.multiplier
self.multiplier += 1
self.score_timer = 10
return reward
return 0
def state(self) -> np.ndarray:
state = np.zeros((10, 10, 6), dtype=bool)
row = int(self.y) // 5
state[row, :3, 0] = True
state[row, :3, 3] = self.on_bridge
state[8:, :, 2] = True
for bridge in self.bridges:
for column in range(10):
state[7, column, 1] |= column * 15 < bridge.x + bridge.length and (column + 1) * 15 > bridge.x
state[0, :3, 4] = self.pressed, self.jumping, self.vy < 0
for row, value in enumerate((self.steps, self.multiplier, self.score_timer)):
for bit in range(9):
state[row, bit, 5] = bool(value & (1 << bit))
return state
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