Solving Problems by Searching 吉建民 USTC jianminOustc.edu.cn 2022年3月6日 4口◆4⊙t1三1=，￥9QC
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Solving Problems by Searching 吉建民 USTC jianmin@ustc.edu.cn 2022 年 3 月 6 日
Used Materials Disclaimer:本课件采用了S.Russell and P.Norvig's Artificial Intelligence-A modern approach slides,徐林莉老师课件和其他网 络课程课件，也采用了GitHub中开源代码，以及部分网络博客 内容 口卡4三4色进分QC
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Used Materials Disclaimer: 本课件采用了 S. Russell and P. Norvig’s Artificial Intelligence –A modern approach slides, 徐林莉老师课件和其他网 络课程课件，也采用了 GitHub 中开源代码，以及部分网络博客 内容
回顾 Agents interact with environments through actuators and sensors The performance measure evaluates the environment sequence A perfectly rational agent maximizes expected performance PEAS descriptions define task environments Environments are categorized along several dimensions: observable?deterministic?episodic?static?discrete? single-agent? Several basic agent architectures exist: reflex,reflex with state,goal-based,utility-based 4口◆4⊙t1三1=，￥9QC
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 回顾 ▶ Agents interact with environments through actuators and sensors ▶ The performance measure evaluates the environment sequence ▶ A perfectly rational agent maximizes expected performance ▶ PEAS descriptions define task environments ▶ Environments are categorized along several dimensions: ▶ observable? deterministic? episodic? static? discrete? single-agent? ▶ Several basic agent architectures exist: ▶ reflex, reflex with state, goal-based, utility-based
Table of Contents Problem-solving Agents Searching for Solutions Uninformed Search Strategies 口卡4三，4色，进分QC
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Table of Contents Problem-solving Agents Searching for Solutions Uninformed Search Strategies
Problem-solving Agents:Agents that Plan Ahead Problem-solving agents decide based on evaluating future action sequences Search algorithms typically assume Known,deterministic transition model Discrete states and actions Fully observable Atomic representation States of the world are considered as wholes,with no internal structure visible to the problem-solving algorithms Usually have a definite goal Optimal:Achieve goal at least cost Problem-solving agents:a kind of goal-based agent using atomic representations that use more advanced factored or structured representations are usually called planning agents 日◆4日4三+1=，￥9QC
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Problem-solving Agents: Agents that Plan Ahead ▶ Problem-solving agents decide based on evaluating future action sequences ▶ Search algorithms typically assume ▶ Known, deterministic transition model ▶ Discrete states and actions ▶ Fully observable ▶ Atomic representation ▶ States of the world are considered as wholes, with no internal structure visible to the problem-solving algorithms ▶ Usually have a definite goal ▶ Optimal: Achieve goal at least cost Problem-solving agents: a kind of goal-based agent using atomic representations ▶ that use more advanced factored or structured representations are usually called planning agents