G-逻辑智能体-人工智能(AI).ppt

逻辑智能体 Logical Agents （知识，推理） Chapter 7 “Thinking Rationally” Computational models of human “thought” processes Computational models of human behavior Computational systems that “think” rationally Computational systems that behave rationally 逻辑智能体 逻辑（基于知识）智能体 Logic (Knowledge-Based) agents 通用知识 ＋ 当前的感知 在决定动作前推理(infer)出当前状态的隐含状况 这在部分可观察环境中至关重要 要点 基于知识的智能体 Knowledge-based agents 怪兽世界 Wumpus world 逻辑 Logic in general 命题逻辑与一阶逻辑 Propositional and first-order logic 推理，合法，等价，可满足 模式推理 Reasoning patterns 归结 Resolution 前向/后向链 Forward/backward chaining 知识和推理 Knowledge Reasoning 知识库 knowledge base (KB): 智能体所知道的一系列知识 根据推理的规则（ rules of inference ）由旧的事实推出新事实 逻辑 Logic 表示知识，并进行推理 知识库 Knowledge Base 知识库 : 一系列 语句 以一种 知识表示语言 的格式 来 表示（有关世界的）断言 基于知识的智能体: Tell it what it needs to know. Ask it what to do ? 应遵循推理的规则由知识库得到答案 通用的基于知识智能体 Generic KB-Based Agent 基于知识智能体的特性 能够: 表示状态和动作 综合新的感知 更新关于世界的内部认识 推导出世界的隐含性质 推导出适合的动作 Mine Sweeper Design a logical agent to play minesweeper PEAS Analysis Mine Sweeper Performance measure +1 for each mine correctly identified, -1 for incorrectly identifying a mine, -1000 for selecting a location containing a mine, +1000 for identifying all mines. Environment 9 x 9 board, each square has a mine with probability 0.1 Actuators Agent can mark a location as containing a mine, can mark a location as unknown, or select a location for viewing Sensors Agent can sense the number of mines surrounding adjacent locations Agent knows number of mines remaining 怪兽问题 Wumpus World 怪兽问题的 PEAS 描述 Performance measure 性能度量 gold: +1000, death: -1000 -1 per step, -10 for using the arrow Environment 环境 Squares adjacent to wumpus are smelly Squares adjacent to pit are breezy Glitter iff gold is in the same square Shooting kills wumpus if you are facing it. It screams Shooting uses up the only arrow Grabbing picks up gold if in same square Releasing drops the gold in same square You bump if you walk into a wall Sensors 传感: Stench, Breeze, Glitter, Bump, Scream