القائمة
Score candidate movement directions by average distance to nearby opponents and pick the safest path for ball-carrying agents in game AI
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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| name | tabular-opponent-avoidance-scoring |
| description | Score candidate movement directions by average distance to nearby opponents and pick the safest path for ball-carrying agents in game AI |
When an agent controls the ball in a game AI, choosing which direction to advance requires evaluating opponent density ahead. Score each candidate direction (right, top-right, bottom-right) by the average distance to opponents in that sector. Pick the direction with the greatest average distance — or trigger a long pass if all directions are blocked (too many opponents nearby).
import numpy as np
def avg_distance_to_opponents(obs, target_x, target_y):
opponents = obs["right_team"]
dists = [np.sqrt((ox - target_x)**2 + (oy - target_y)**2) for ox, oy in opponents]
nearby = [d for d in dists if d < 0.05]
return np.mean(nearby) if nearby else 2.0, len(nearby)
def pick_direction(obs, player_x, player_y):
directions = {
"right": (player_x + 0.01, player_y),
"top_right": (player_x + 0.01, player_y - 0.01),
"bottom_right": (player_x + 0.01, player_y + 0.01),
}
best_dir, best_dist = "right", 0
total_nearby = 0
for name, (tx, ty) in directions.items():
dist, count = avg_distance_to_opponents(obs, tx, ty)
total_nearby += count
if dist > best_dist:
best_dist = dist
best_dir = name
if total_nearby >= 3:
return "high_pass" # surrounded — clear the ball
return best_dir