《Artificial Intelligence：A Modern Approach》教学资源（讲义，英文版）chapter03

PROBLEM SOLVING AND SEARCH CHAPTER 3 Chapter 3 1

Problem solving and search Chapter 3 Chapter 3 1

Reminders Assignment 0 due 5pm today Assignment 1 posted,due 2/9 Section 105 will move to 9-10am starting next week Chapter 3 2

Reminders Assignment 0 due 5pm today Assignment 1 posted, due 2/9 Section 105 will move to 9-10am starting next week Chapter 3 2

Outline Problem-solving agents ◇Problem types ◇Problem formulation ◇Example problems Basic search algorithms Chapter 33

Outline ♦ Problem-solving agents ♦ Problem types ♦ Problem formulation ♦ Example problems ♦ Basic search algorithms Chapter 3 3

Problem-solving agents Restricted form of general agent: function SIMPLE-PROBLEM-SOLVING-AGENT(percept)returns an action static:seg,an action sequence,initially empty state,some description of the current world state goal,a goal,initially null problem,a problem formulation stateUPDATE-STATE(state,percept) if seg is empty then goal-FORMULATE-GOAL(state) problem+FORMULATE-PROBLEM(state,goal) seg-SEARCH(problem) action-RECOMMENDATION(seg,state) seg-REMAINDER(seg,state) return action Note:this is offline problem solving;solution executed "eyes closed." Online problem solving involves acting without complete knowledge. Chapter 3 4

Problem-solving agents Restricted form of general agent: function Simple-Problem-Solving-Agent( percept) returns an action static: seq, an action sequence, initially empty state, some description of the current world state goal, a goal, initially null problem, a problem formulation state ← Update-State(state, percept) if seq is empty then goal ←Formulate-Goal(state) problem ←Formulate-Problem(state, goal) seq ← Search( problem) action ←Recommendation(seq,state) seq ← Remainder(seq,state) return action Note: this is offline problem solving; solution executed “eyes closed.” Online problem solving involves acting without complete knowledge. Chapter 3 4

Example:Romania On holiday in Romania;currently in Arad. Flight leaves tomorrow from Bucharest Formulate goal: be in Bucharest Formulate problem: states:various cities actions:drive between cities Find solution: sequence of cities,e.g.,Arad,Sibiu,Fagaras,Bucharest Chapter 3 5

Example: Romania On holiday in Romania; currently in Arad. Flight leaves tomorrow from Bucharest Formulate goal: be in Bucharest Formulate problem: states: various cities actions: drive between cities Find solution: sequence of cities, e.g., Arad, Sibiu, Fagaras, Bucharest Chapter 3 5

Example:Romania ▣Oradea 71 Neamt 口Zerind 87 75 151 ▣lasi Arad 140 Sibiu 92 99 Fagaras 118 ▣ ▣Vaslui 80 女Timisoara Rimnicu Vilcea O 142 111 211 口Lugj 97 Pitesti 70 口 98 Mehadia 146 85 Urziceni ▣Hirsova 101 75 138 86 Bucharest Dobreta☐ 120 ▣ Craiova 90 Eforie Giurgiu Chapter 3 6

Example: Romania Giurgiu Urziceni Hirsova Eforie Neamt Oradea Zerind Arad Timisoara Lugoj Mehadia Dobreta Craiova Sibiu Fagaras Pitesti Vaslui Iasi Rimnicu Vilcea Bucharest 71 75 118 111 70 75 120 151 140 99 80 97 101 211 138 146 85 90 98 142 92 87 86 Chapter 3 6

Problem types Deterministic,fully observable-single-state problem Agent knows exactly which state it will be in;solution is a sequence Non-observable=conformant problem Agent may have no idea where it is;solution(if any)is a sequence Nondeterministic and/or partially observable=contingency problem percepts provide new information about current state solution is a contingent plan or a policy often interleave search,execution Unknown state space exploration problem ("online") Chapter 3 7

Problem types Deterministic, fully observable =⇒ single-state problem Agent knows exactly which state it will be in; solution is a sequence Non-observable =⇒ conformant problem Agent may have no idea where it is; solution (if any) is a sequence Nondeterministic and/or partially observable =⇒ contingency problem percepts provide new information about current state solution is a contingent plan or a policy often interleave search, execution Unknown state space =⇒ exploration problem (“online”) Chapter 3 7

Example:vacuum world Single-state,start in #5.Solution?? -Q 2 哪 哪 3 8 Q 娜 -Q Chapter 3 8

Example: vacuum world Single-state, start in #5. Solution?? 1 2 3 4 5 6 7 8 Chapter 3 8

Example:vacuum world Single-state,start in #5.Solution?? Right,Suck 1 -Q 2 绑 Conformant,start in (1,2,3,4,5,6,7,8 e.g.,Right goes to (2,4,6,8).Solution?? Q Q 粥 5 -Q 部 8 =Q Chapter 3 9

Example: vacuum world Single-state, start in #5. Solution?? [Right, Suck] Conformant, start in {1, 2, 3, 4, 5, 6, 7, 8} e.g., Right goes to {2, 4, 6, 8}. Solution?? 1 2 3 4 5 6 7 8 Chapter 3 9

Example:vacuum world Single-state,start in #5.Solution?? Right,Suck Q 哪 哪 Conformant,start in 1,2,3,4,5,6,7,8 e.g.,Right goes to (2,4,6,8).Solution?? 3 8 Right,Suck,Left,Suck 5 -Q ~Q Contingency,start in #5 娜 Murphy's Law:Suck can dirty a clean carpet -Q Local sensing:dirt,location only. Solution.?? Chapter 3 10

Example: vacuum world Single-state, start in #5. Solution?? [Right, Suck] Conformant, start in {1, 2, 3, 4, 5, 6, 7, 8} e.g., Right goes to {2, 4, 6, 8}. Solution?? [Right, Suck,Left, Suck] Contingency, start in #5 Murphy’s Law: Suck can dirty a clean carpet Local sensing: dirt, location only. Solution?? 1 2 3 4 5 6 7 8 Chapter 3 10