第四十四章 WSaiOS Cognitive Learning Engine学习引擎源码实现
第四十四章
WSaiOS Cognitive Learning Engine学习引擎源码实现
44.7 Cognitive Learning Engine核心控制器源码实现
在44.6节中，我们完成了：
- Policy对象模型；
- Rule → Policy转换；
- Policy Evaluation；
- Policy Selection；
- Policy Evolution。
至此，WSaiOS Learning Engine已经具备：
Experience
↓
Pattern
↓
Knowledge
↓
Rule
↓
Policy
但是以上模块仍然是独立组件。
真正的系统需要一个统一控制核心：
负责协调所有学习模块的运行。
因此设计：
Cognitive Learning Engine Core
认知学习引擎核心控制器
44.7.1 Learning Engine Core定位
Learning Engine Core是整个学习系统的Runtime控制中心。
职责：
- 接收Feedback输入；
- 创建Experience；
- 调用Pattern Learning；
- 更新Knowledge；
- 生成Rule；
- 优化Policy；
- 输出学习结果。
架构：
Feedback Engine
│
▼
┌────────────────────────┐
│ Cognitive Learning Core │
└────────────────────────┘
│
┌───────────────┼────────────────┐
▼ ▼ ▼
Experience Pattern Knowledge
Learning Learning Learning
│
▼
Rule
│
▼
Policy
│
▼
Decision Engine
44.7.2 Core模块结构
最终：
cognitive_learning/
├── engine.py
├── pipeline.py
├── runtime.py
├── manager.py
├── scheduler.py
├── event_handler.py
├── config.py
│
├── experience/
├── pattern/
├── knowledge/
├── rule/
└── policy/
44.7.3 Learning Pipeline设计
WSaiOS采用：
Cognitive Learning Pipeline
流程：
Feedback Event
│
▼
Experience Builder
│
▼
Experience Analyzer
│
▼
Pattern Discovery
│
▼
Knowledge Builder
│
▼
Rule Evolution
│
▼
Policy Optimization
│
▼
Learning Result
44.7.4 Learning Pipeline源码
文件：
pipeline.py代码：
class LearningPipeline:
def __init__(
self,
experience,
pattern,
knowledge,
rule,
policy
):
self.experience_engine=experience
self.pattern_engine=pattern
self.knowledge_engine=knowledge
self.rule_engine=rule
self.policy_engine=policy
def process(
self,
feedback
):
# Feedback → Experience
exp=(
self.experience_engine
.create(
feedback
)
)
# Experience → Pattern
pattern=(
self.pattern_engine
.learn(
exp
)
)
# Pattern → Knowledge
knowledge=(
self.knowledge_engine
.learn(
pattern
)
)
# Knowledge → Rule
rule=(
self.rule_engine
.evolve(
knowledge
)
)
# Rule → Policy
policy=(
self.policy_engine
.optimize(
rule
)
)
return {
"experience":
exp,
"pattern":
pattern,
"knowledge":
knowledge,
"rule":
rule,
"policy":
policy
}
44.7.5 Learning Engine核心类
文件：
engine.py
代码：
class CognitiveLearningEngine:
def __init__(self):
self.pipeline=None
self.running=False
def initialize(
self,
pipeline
):
self.pipeline=pipeline
self.running=True
print(
"[Cognitive Learning Engine Ready]"
)
def learn(
self,
feedback
):
if not self.running:
raise Exception(
"Learning Engine not running"
)
return self.pipeline.process(
feedback
)
def shutdown(self):
self.running=False
print(
"[Learning Engine Shutdown]"
)
44.7.6 Learning Runtime运行管理
Learning Engine需要生命周期管理。
文件：
runtime.py代码：
class LearningRuntime:
def __init__(
self,
engine
):
self.engine=engine
def start(self):
self.engine.running=True
def stop(self):
self.engine.shutdown()
def status(self):
return {
"running":
self.engine.running
}
44.7.7 Feedback事件接收
Learning Engine通过Event Bus接收：
Feedback Event
│
▼
Learning Event Handler
│
▼
Learning Engine
文件：
event_handler.py代码：
class LearningEventHandler:
def __init__(
self,
engine
):
self.engine=engine
def handle(
self,
event
):
return self.engine.learn(
event.data
)
44.7.8 Learning Manager
负责统一管理：
Engine
Pipeline
Runtime
Events
Memory
代码：
class LearningManager:
def __init__(self):
self.engines={}
def register(
self,
name,
engine
):
self.engines[name]=engine
def get(
self,
name
):
return self.engines.get(
name
)
44.7.9 完整学习示例
输入：
Feedback：
{
"task":
"Generate SEO Content",
"result":
"success",
"quality":
0.95
}
执行：
Feedback
↓
Experience
↓
Pattern
↓
Knowledge
↓
Rule
↓
Policy
输出：
{
"policy":
{
"strategy":
"structured semantic generation",
"confidence":
0.91
}
}
44.7.10 Learning Engine与WSaiOS Runtime集成
整体：
WSaiOS Runtime
│
├── Execution Engine
│
├── Feedback Engine
│
└── Learning Engine
│
▼
Policy Update
│
▼
Decision Engine
调用：
learning_engine.learn(
feedback_event
)
44.7.11 Core设计原则
1. 模块解耦
Core不直接实现学习算法。
只负责：
协调。
2. Pipeline可替换
未来可以替换：
- Symbolic Learning；
- Statistical Learning；
- Hybrid Learning。
3. 全流程可追踪
每次学习：
记录：
Input
↓
Transformation
↓
Output
4. 支持长期运行
适用于：
WSaiOS：
Local First Architecture。
44.7 本节总结
本节完成：
Cognitive Learning Engine核心控制器源码实现
实现：
✅ Learning Pipeline
✅ Learning Engine Core
✅ Runtime管理
✅ Event Handler
✅ Learning Manager
✅ Feedback连接
✅ Experience → Policy完整闭环
当前第四十四章进度：
44.1 Learning Engine总体架构 ✅
44.2 Experience Learning ✅
44.3 Pattern Learning ✅
44.4 Knowledge Learning ✅
44.5 Rule Evolution ✅
44.6 Policy Optimization ✅
44.7 Learning Engine Core ✅
下一节：
44.8 Learning Memory与Knowledge Consolidation源码实现
重点：
- Long Term Learning Memory
- Short Term Experience Memory
- Knowledge Consolidation
- Memory Retrieval
- Forgetting Mechanism
- Cognitive Memory Integration
进入WSaiOS：
学习 → 记忆 → 长期能力形成
阶段。