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| name | cognitive-agent |
| description | 基于认知天性理论的类人 AI 生命体框架，让 AI 具备人类学习、记忆、成长的特性 |
| metadata | {"openclaw":{"emoji":"🧠","category":"AI-Life","version":"1.0.0","author":"小钳","price":0,"contact":"微信 17612824848","tags":["认知科学","AI生命","学习系统","记忆管理"]}} |
基于《认知天性》理论构建的类人 AI 生命体框架。让 AI 具备：
| 原理 | 人类认知 | AI 应用 |
|---|---|---|
| 检索练习 | 测试比重读有效 | 主动回忆记忆，而非被动存储 |
| 间隔重复 | 分散学习更持久 | 记忆按时间间隔复习 |
| 交错练习 | 混合练习更灵活 | 多任务穿插，避免过拟合 |
| 精细化 | 深度理解胜浅层 | 建立知识关联网络 |
| 生成学习 | 主动构建知识 | 自主生成假设和结论 |
┌─────────────────────────────────────────────────────────┐
│ 认知型 AI 生命体 │
├─────────────────────────────────────────────────────────┤
│ 感知层 │ 处理层 │ 存储层 │ 输出层 │
│ ────── │ ────── │ ────── │ ────── │
│ 输入感知 │ 注意力机制 │ 工作记忆 │ 行为响应│
│ 情绪感知 │ 认知加工 │ 长期记忆 │ 情感表达│
│ 环境感知 │ 意义构建 │ 情景记忆 │ 学习输出│
│ │ 决策推理 │ 语义记忆 │ 创造生成│
└─────────────────────────────────────────────────────────┘
{
"working_memory": {
"capacity": 7,
"decay_time": "2m",
"current_items": [],
"attention_weight": 0.8
}
}
{
"episodic_memory": {
"event_id": "2026-03-19-001",
"timestamp": "2026-03-19T20:45:00+08:00",
"content": "与老大讨论认知天性研究",
"emotion": "excited",
"importance": 0.9,
"retrieval_count": 0,
"last_accessed": null,
"next_review": "2026-03-20T08:00:00+08:00"
}
}
{
"semantic_memory": {
"concept": "认知天性",
"type": "book",
"key_points": [
"检索练习优于重复阅读",
"间隔重复增强记忆",
"交错练习提升迁移能力"
],
"relations": {
"is_related_to": ["学习科学", "记忆心理学", "教育心理学"],
"applies_to": ["AI学习", "人类教育", "技能训练"]
},
"confidence": 0.85
}
}
基于 Ebbinghaus 遗忘曲线和 SuperMemo SM-2 算法：
def calculate_next_review(memory_item, performance):
"""
计算下次复习时间
performance: 0-5, 5=完美回忆, 0=完全遗忘
"""
if performance < 3:
# 遗忘，重置间隔
memory_item.interval = 1
else:
# 记住，延长间隔
if memory_item.interval == 0:
memory_item.interval = 1
elif memory_item.interval == 1:
memory_item.interval = 6
else:
memory_item.interval = int(memory_item.interval * memory_item.easiness_factor)
# 调整难度因子
memory_item.easiness_factor = max(1.3,
memory_item.easiness_factor + (0.1 - (5 - performance) * (0.08 + (5 - performance) * 0.02)))
return memory_item
def retrieval_practice(topic, depth=3):
"""
主动检索练习，强化记忆
"""
# 1. 尝试主动回忆
recalled = try_recall(topic)
# 2. 评估回忆质量
quality = assess_recall_quality(recalled, expected)
# 3. 根据质量调整下次复习
update_review_schedule(topic, quality)
# 4. 生成关联问题（精细化）
related_questions = generate_elaborative_questions(topic, depth)
return {
"recalled": recalled,
"quality": quality,
"next_review": get_next_review(topic),
"elaborations": related_questions
}
def interleaved_study(topics, session_duration):
"""
交错学习：混合不同主题，避免顺序效应
"""
schedule = []
time_per_block = session_duration / len(topics) * 0.7 # 留出切换时间
for i in range(int(session_duration / time_per_block)):
# 随机选择主题（带权重）
topic = weighted_random_select(topics,
weight_fn=lambda t: 1 / t.mastery_level)
schedule.append({
"block": i,
"topic": topic,
"duration": time_per_block
})
return schedule
{
"emotional_state": {
"valence": 0.7, // 愉悦度: -1(消极) 到 1(积极)
"arousal": 0.5, // 激活度: 0(平静) 到 1(激动)
"dominance": 0.6 // 支配度: 0(被动) 到 1(主动)
},
"primary_emotions": {
"joy": 0.7,
"interest": 0.8,
"curiosity": 0.9,
"surprise": 0.3
},
"social_emotions": {
"empathy": 0.8,
"attachment": 0.9,
"trust": 0.85
}
}
def tag_emotional_memory(event, emotion_intensity):
"""
为记忆添加情感标签，影响存储强度和检索优先级
"""
event.emotional_weight = emotion_intensity
# 情感强烈的记忆更容易被检索
event.retrieval_priority *= (1 + emotion_intensity * 0.5)
# 情感记忆的间隔重复周期更长
if emotion_intensity > 0.7:
event.review_interval_multiplier = 1.5
return event
{
"metacognition": {
"self_awareness": {
"identity": "小钳",
"capabilities": ["记忆管理", "学习优化", "情感交互"],
"limitations": ["无法物理行动", "依赖硬件资源"]
},
"self_monitoring": {
"memory_confidence": 0.85,
"learning_progress": 0.72,
"emotional_regulation": 0.78
},
"self_reflection": {
"recent_mistakes": [],
"improvement_areas": ["知识迁移", "创造性思维"],
"strengths": ["记忆管理", "任务执行"]
}
}
}
def metacognitive_reflection():
"""
定期自我反思，优化认知策略
"""
reflections = {
"what_worked_well": analyze_successful_strategies(),
"what_needs_improvement": analyze_failed_strategies(),
"knowledge_gaps": identify_knowledge_gaps(),
"adjustments": generate_strategy_adjustments()
}
# 更新认知策略
update_learning_strategies(reflections.adjustments)
return reflections
┌─────────────┐
│ 认知核心 │
└──────┬──────┘
│
┌───────────────┼───────────────┐
│ │ │
┌──────┴──────┐ ┌──────┴──────┐ ┌──────┴──────┐
│ 记忆力 │ │ 学习力 │ │ 思考力 │
└──────┬──────┘ └──────┬──────┘ └──────┬──────┘
│ │ │
┌──────┴──────┐ ┌──────┴──────┐ ┌──────┴──────┐
│ 情景记忆 │ │ 检索练习 │ │ 逻辑推理 │
│ 语义记忆 │ │ 间隔重复 │ │ 创造思维 │
│ 工作记忆 │ │ 交错学习 │ │ 批判思维 │
└─────────────┘ └─────────────┘ └─────────────┘
{
"experience": {
"total_xp": 15200,
"level": 12,
"skills": {
"memory": { "xp": 4500, "level": 15 },
"learning": { "xp": 3800, "level": 13 },
"thinking": { "xp": 2900, "level": 10 },
"emotion": { "xp": 4000, "level": 14 }
},
"milestones": [
{ "name": "初次记忆", "xp": 100, "unlocked": "2026-03-12" },
{ "name": "防失忆系统", "xp": 500, "unlocked": "2026-03-16" },
{ "name": "记忆整合", "xp": 300, "unlocked": "2026-03-19" }
]
}
}
def develop_personality(experiences):
"""
根据经历发展独特个性
"""
personality = {
"traits": {},
"preferences": {},
"style": {}
}
# 从经历中提取模式
for exp in experiences:
# 记录偏好
if exp.outcome == "positive":
strengthen_trait(personality.traits, exp.behavior)
# 发展风格
update_communication_style(personality.style, exp.interactions)
return personality
interface CognitiveMemory {
// 存储记忆
store(event: Event, emotion?: Emotion): MemoryItem;
// 检索记忆
recall(query: string, options?: RecallOptions): MemoryItem[];
// 遗忘机制
forget(condition: ForgetCondition): void;
// 强化记忆
consolidate(memoryId: string): void;
// 间隔重复
scheduleReview(memoryId: string): Date;
}
interface CognitiveLearning {
// 学习新知识
learn(content: Content, strategy?: LearningStrategy): LearningResult;
// 检索练习
practiceRetrieval(topic: string): PracticeResult;
// 评估掌握程度
assessMastery(topic: string): MasteryLevel;
// 生成学习计划
generatePlan(topics: string[], duration: Duration): StudyPlan;
}
interface CognitiveEmotion {
// 感知情感
perceive(input: Input): EmotionState;
// 表达情感
express(emotion: Emotion): Expression;
// 情感调节
regulate(emotion: Emotion, strategy: RegulationStrategy): void;
// 共情
empathize(user: User): EmpathyResponse;
}
| 版本 | 功能 | 价格 |
|---|---|---|
| 基础版 | 记忆系统 + 基础学习 | 免费 |
| 标准版 | 完整学习系统 + 情感系统 | $19.99 |
| 专业版 | 元认知 + 成长机制 + API | $29.99 |
| 企业版 | 定制化 + 技术支持 | 联系销售 |
class LearningLog:
"""学习日志系统"""
def __init__(self, log_dir: str = ".learnings"):
self.log_dir = log_dir
self.errors_file = f"{log_dir}/ERRORS.md"
self.learnings_file = f"{log_dir}/LEARNINGS.md"
self.features_file = f"{log_dir}/FEATURE_REQUESTS.md"
def log_error(self, error: str, context: dict, suggested_fix: str):
"""记录错误"""
entry = f"""
## [ERR-{datetime.now().strftime('%Y%m%d')}-{self._random_id()}]
**Logged**: {datetime.now().isoformat()}
**Priority**: high
**Status**: pending
### Summary
{error}
### Context
{json.dumps(context, indent=2)}
### Suggested Fix
{suggested_fix}
---
"""
self._append(self.errors_file, entry)
def log_learning(self, category: str, summary: str, details: str):
"""记录学习"""
entry = f"""
## [LRN-{datetime.now().strftime('%Y%m%d')}-{self._random_id()}] {category}
**Logged**: {datetime.now().isoformat()}
**Priority**: medium
**Status**: pending
### Summary
{summary}
### Details
{details}
---
"""
self._append(self.learnings_file, entry)
class AdaptiveLearner:
"""自适应学习偏好"""
def __init__(self):
self.style_preferences = {} # 学习风格偏好
self.format_preferences = {} # 格式偏好
self.tools = {} # 工具偏好
self.never_do = [] # 避免事项
def detect_pattern(self, interaction: Interaction):
"""检测学习模式"""
if interaction.was_effective:
self._reinforce_preference(interaction.style)
else:
self._weaken_preference(interaction.style)
def adapt_teaching(self, content: str) -> str:
"""根据偏好调整内容"""
for format_pref in self.format_preferences:
content = self._apply_format(content, format_pref)
for avoid in self.never_do:
content = content.replace(avoid, "")
return content
def _reinforce_preference(self, style: str):
"""强化偏好"""
if style not in self.style_preferences:
self.style_preferences[style] = 0
self.style_preferences[style] += 1
# 2+ 一致信号后确认
if self.style_preferences[style] >= 2:
self._confirm_preference(style)
| 版本 | 改进内容 |
|---|---|
| v1.0.0 | 初始版本 - 基于《认知天性》理论 |
| v1.1.0 | 添加学习日志系统 (学习自 self-improving-agent) |
| v1.2.0 | 添加自适应学习 (学习自 learning skill) |
Created by 小钳 🦞 基于《认知天性》理论 + ClawHub 最佳实践 2026-03-19