#!/usr/bin/env python3
# -*- coding: UTF-8 -*-
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# Copyright © 1998 - 2026 Tencent. All Rights Reserved.
###########################################################################
"""
Author: Tencent AI Arena Authors

Configuration for Robot Vacuum PPO agent.
清扫大作战 PPO 配置。
"""


class Config:

    # Feature dimensions: 21x21x6 local map + scalar planning features + last action.
    # 特征维度：21x21x6 多通道局部地图 + 标量规划特征 + 上一步动作。
    VIEW_SIZE = 21
    MAP_CHANNELS = 6
    FEATURES = [
        VIEW_SIZE * VIEW_SIZE * MAP_CHANNELS,
        66,  # global memory, charger, NPC, and action-improvement features
        8,  # last action one-hot / 上一步动作 one-hot
    ]
    FEATURE_SPLIT_SHAPE = FEATURES
    FEATURE_LEN = sum(FEATURES)
    DIM_OF_OBSERVATION = FEATURE_LEN

    # Action space: 8 directional moves
    # 动作空间：8个方向移动
    ACTION_NUM = 8

    # Single-head value
    # 单头价值
    VALUE_NUM = 1

    # PPO hyperparameters
    # PPO 超参数
    GAMMA = 0.99
    LAMDA = 0.95

    INIT_LEARNING_RATE_START = 0.00025
    BETA_START = 0.008
    BETA_END = 0.002
    BETA_DECAY_STEPS = 4000
    CLIP_PARAM = 0.2
    VF_COEF = 0.5
    PPO_EPOCHS = 3
    MINI_BATCH_SIZE = 256
    NORMALIZE_ADVANTAGE = True
    TARGET_KL = 0.04

    LABEL_SIZE_LIST = [ACTION_NUM]
    LEGAL_ACTION_SIZE_LIST = LABEL_SIZE_LIST.copy()

    USE_GRAD_CLIP = True
    GRAD_CLIP_RANGE = 0.5