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1 ۱۰ p Classical Planning [ ¾\, ³ «}1?0`1 gã\ac ċ i] ¼ ] l±0\ 0a¼G 1 l±0\

2 ³ p j³½ Âi ¾cÃ`Tay

3 3 PLANNING? Ã ½[ف?1ÃEi\ ¾0a? 1½ k b0 ¾cÃ`Tay ¾0 1>±\ F 1Ã ¾ Æh ¾cÃ`Tay Planning

4 4 ] ¾cÃ`Tay ¾`1 ARCHITECTURE OF A PLANNER ½[ف Goal wâv E 1W State of Env. ¾1½ k Possible Actions ] ¾cÃ`Tay Planner Tay Plan

5 5 Âi ¾cÃ`Tay À1½wÂV D1Âq³p[ 1 aã_c ]½1l Fully Observable Á 1 G Single-agent Á x [ Deterministic Á x Episodic 1FhÃ0 Static Fhh Discrete ]m F[1 m Known ÁÇcO aã_c ]½1l Partially Observable Á 1 ] S Multiagent Á [ 1 G0 Stochastic À0 1>±\ Sequential 1óC Dynamic Fi³ÂC Continuous F[1 m1± Unknown

6 6 ¾cÃ`Tay 1Jل «Âi? ¾ F à ² ċb³ ċaâm ¾ ¼G č Æh Ċ]±`³[ Eh m >i1 1± bay? \`0]±1Fi0 ¾³NFhO ¾1½ «FÃ`³ 0 After-the-fact ½[ف ³ b2 ² 1½ ÂFhÃ`³Â½ \³? 1 1± ]i` a ±?

7 7 ĝ¾cã`tayğ 1? ĝ³nfhoğ ¾ hã1 ³NFhO b0 \1 Fi0 1? Æh W ¾1½ 1 Ĉ] Fh½ v³?a 1½ k ª0] ĉ] ± m²` 0` Ã0 >[ E 1W ¾1t Ãa G v³?a ¾1½ k Relevant Actions ĈEhÂS <³[ ÂFhÃ`³h½?1G à ĉ\³m ¼G \`³ a½ ¾0a? 1h±0 à wi³g ]Ã1? Ĉ\a ÃcNG 0` Æh ]Ã1? ±³ S ċ] Fh½ aã_c ÃcNG Ø1>Ãa G [ 0² ¾1±\ Ç1h aflâ? ĉ] ± `1 m2 0` Æh b0 ¾`1F[1i ±³ Q½ E 1W ¾1t Ãa G 1 0 <³[ ÂFhÃ`³Â½?1G Good Heuristic Function Æh ¾ ÃcNG Problem Decomposition

8 8 ĝ¾cã`tayğ 1? ĝ³nfhoğ ¾ hã1 Ei0 ªb, ] ¾cÃ`Tay 1 ¾0a? R±2 1½E 1W ² 1½ k Â? 1 G? b1â± Ċ] \²]V 0` E 1W à `\ 1¼±2 ¾a `1? ]±`0\ Ã1½] 2 C ² 1½ ¾] b1â± ċ1½ k v³?a ¾1½ k Relevant Actions ³xف ¾1½ ÂFhÃ`³Â½ \³O² D`²au? ½[ف ¾0a? ³xف ¾1½ Tay \1NÃ0? ½[ف Fh D`³q? aãb ½[ف½ 1 W D`²au ĊEi0 Fh 2 ¾0cO0 aã1i aflâ? b0 1±\ ¾0cO0 aflâ? <³[ ÂFhÃ`³Â½?1G Good Heuristic Function Æh ¾ ÃcNG Problem Decomposition

9 9 ĝ¾cã`tayğ 1? ĝ³nfhoğ ¾ hã1 ¾cÃ`Tay \`0]±1Fi0 ¾³NFhO Planning Standard Search x ¾1½ O 1½ \0\ 1 F[1i 1½E 1W States 1½] 2a? ď 1½vamkÂC ¾0`0\ x ¾1½ O 1½ k ¾²` Ã1½]Â[ 1? ¾0 1>±\ ] ] Ãb1 2 E 1W b0 ¾0 1>±\ 1½ k Actions ½[ف Goal Tay Plan

10 10 ¾cÃ`Tay ¾ Æh E 1W \`0]±1Fi0 ¾³NFhO ¾cÃ`Tay ¾ Æh 1Âi ¾ > O Ã če 1W b2 ³ ½[فč ÂÂ G ½[ف \³? 1Ã ½[ف UÃaq 1Ã u čę a Ě E 1W Ã \³>± 1½ pâp[ aã\1 b0 ¾`0\a? če 1W x ¾1½ O D`³q? ½[فč ³ b2

11 11 ¾cÃ`Tay 1?b PLANNING LANGUAGE PDDL Planning Domain Definition Language ¾cÃ`Tay ¾ 0\ Ãa G 1?b \³m 1Â? ¾cÃ`Tay 1?b `\ R±2 b2 ³ ½[ف Goal Test 1 EÃ\²]V Restrictive Enough 1½ k ¾ NÂF± Results of Actions v³?a ¾1½ «FÃ`³ 0 ¾] 2`1 ¾0a? 1 EÃ\²]V \³O³ ¾1½ k Available Actions ¾cÃ`Tay 1?b à ¾0a? ªb, ¾1½ eã² 1 Ã1i` Expressive Enough Ãb1 2 E 1W Initial State Ç1h b0 ¾0 \afh ~0³±0 Âq³G 1 Ã1i`

12 12 \±1¾? ³ ک½ 1 BLOCKS WORLD حالت هدف حالت ا غازىن č«ã`0\ b1â± aãb ³ Vل ¾1½ ª1±? wâv Ã1 ±b1? ¾0a? č, 1? m?1x? ³ ک½ 1 ¾1±\ ¾0a? FOL Ã1 ±b1?

13 13 PDDL: REPRESENTATION OF STATES ¾cÃ`Tay ¾ 0\ Ãa G 1?b 1½E 1W Ã1 ±b1? PDDL?1G b0 \0b2 ²  b ¾1½ «G0 x E 1W Fh? ¾1±\ ra Closed-World Assumption Ċ\³m ra false ċ]m1? ] 1± E 1W `\ G0 a½

14 14 PDDL: REPRESENTATION OF GOAL ¾cÃ`Tay ¾ 0\ Ãa G 1?b Ã1 ±b1? ½[ف PDDL ½[ف n1[ E 1W à ċ] 1u`0 0` g ½[ف à s E 1W à a 0 Ċ]m1? ęa Ã\ ¾1½ «G0 ]Ã1m ²Ě g ¾1½ «G0 ¾ ½ 1m s

15 15 PDDL: REPRESENTATION OF ACTIONS ¾cÃ`Tay ¾ 0\ Ãa G 1?b 1½k Ã1 ±b1? Ċ]m1? ak0 ² vamkâc PDDL ċª1± à ¾0`0\ k a½ 1½ k k Action ª1± Name vamkâc pre-condition ak0 effect ę]m1? 1 ³ `2 ¾0`0\ ]±0³G Ě ª1± ] m1? true ]Ã1? Ã1½ E [ 0² Eh Ċ\³m 0aO0 ]±0³F? k 1G k ¾0aO0 b0 q1w D0a G Eh W _ف Delete List 1u0 Eh Add List č 0aFÂل½ 1 ¾ Ċ] Fh± true a Ã\ k ª1N±0 b0 gc Ã1½ E [ 0² če>j 0aFÂل½ 1 ¾ Ċ]±³m true k ª1N±0 b0 gc Ã1½ E [ 0² Ċ]m1? 1½a F ¾²1W ]±0³G ċk kz? a½

16 16 PDDL: REPRESENTATION OF ACTIONS ¾cÃ`Tay ¾ 0\ Ãa G 1?b `0\³ ± `\ kã1 ± č1½k Ã1 ±b1? Ċ]m1? ak0 ² vamkâc PDDL ċª1± Ã ¾0`0\ k a½ 1½ k Preconditions Name(args) Effects

17 17 PDDL: REPRESENTATION OF ACTIONS ¾cÃ`Tay ¾ 0\ Ãa G 1?b ] kã1 ± č1½k Ã1 ±b1? Ċ]m1? ak0 ² vamkâc PDDL ċª1± Ã ¾0`0\ k a½ 1½ k Name(args), Preconditions Effects )

18 18 \±1¾? ³ ک½ 1 BLOCKS WORLD حالت هدف حالت ا غازىن č«ã`0\ b1â± aãb ³ Vل ¾1½ ª1±? wâv Ã1 ±b1? ¾0a? č, 1? m?1x? ³ ک½ 1 ¾1±\ ¾0a? FOL Ã1 ±b1?

19 19 ¾cÃ`Tay ¾ 0\ Ãa G 1?b Ã1 ±b1? 1Jل č1½k Ċ]½\ `0a [ y Stack(x,y) k ÅÂm ¾²` ċ\`0\ Ei\ `\ 0` x ÅÂm D1?²` ¾²b1?

20 20 ¾cÃ`Tay ¾ 0\ Ãa G 1?b Ã1 ±b1? 1Jل č1½k Ċ\`0\ a? y UnStack(x,y) k a Ã\ ÅÂm ¾²` b0 0` x ÅÂm D1?²` ¾²b1?

21 21 ¾cÃ`Tay ¾ 0\ Ãa G 1?b Ã1 ±b1? 1Jل č1½k Pickup(x) k Ċ\`0\ a? câ ¾²` b0 0` x ÅÂm D1?²` ¾²b1?

22 22 ¾cÃ`Tay ¾ 0\ Ãa G 1?b Ã1 ±b1? 1Jل č1½k PutDown(x) k Ċ\`0_ câ ¾²` 0` x ÅÂm D1?²` ¾²b1?

23 23 APPLICABILITY OF ACTIONS ¾cÃ`Tay ¾ 0\ Ãa G 1?b 1½k ¾a `1? EÂ?1 [ Ei0 ¾a `1??1[ F 1W `\ k à Ċ] m1? ]m 1u`0 kã1½vamkâc 2 `\ Ċ\³m ¾b1i ±³ ± 0]F?0 k ċ\³? 1½a F ¾²1W k a 0

24 24 APPLICABILITY OF ACTIONS ¾cÃ`Tay ¾ 0\ Ãa G 1?b [ EÂ?1 1Jل č1½k ¾a `1?

25 25 EFFECT OF ACTIONS ¾cÃ`Tay ¾ 0\ Ãa G 1?b 1½k ¾a `1? ak0 čei0 s' E 1W à s E 1W `\ a k ¾0aO0 ak0 s a s' čco? ċei0 s 1 ½ s' Ċ\³m 1u0 s'? ċk ¾ 1u0 Eh b0 «G0 a½ Ċ\³m W _ف s' b0 ċk W _ف Eh b0 «G0 a½ Ċ] ± aââ G 1½ «G0 aã1i `0]

26 26 EFFECT OF ACTIONS ), ¾cÃ`Tay ¾ 0\ Ãa G 1?b 1Jل č1½k ¾a `1? ak0

27 27 Tay PLAN 1>±\ ¾0 b0 Ã??1à Ei\ ¾0a? 1½ k ½[ف ę1½e?1k 1? ]m Ãc Ã1O ¾1½a F 1?Ě x[ Tay Linear Plan ďe[`\ Ã??1ÃEi\ ¾0a? 1½ k b0 0a ½[ف ę W ² vam ¾²1W č x[aâ ¾1½TayĚ x[aâ Tay Non-linear Plan Ď] Fh½ x[aâ ċ [ 0² ]±b ¾1½Tay aflâ? ĕ ĉ] `0\0 0` 1½`1F[1i Ã0 ] ±0³G ± \1i ¾1½ ] ¾cÃ`Tay aj 0 1 0

28 ³ p j³½ Âi ¾cÃ`Tay

29 29 E 1W ¾1t ¾³NFhO = 1 [ `\ ¾cÃ`Tay PLANNING AS STATE-SPACE SEARCH E 1W ¾1t ¾³NFhO = 1 [ `\ ¾cÃ`Tay ]±²` gc ¾ ] ¾cÃ`Tay Regressive (Backward) Planner E 1W ¾1t ¾²`gC ¾³NFhO 1? ]±²` kâc ¾ ] ¾cÃ`Tay Progressive (Forward) Planner E 1W ¾1t ¾²`kÂC ¾³NFhO 1? ]±²` kâc ]±²` gc 0\ b0 Fh ¾1½ ÂFhÃ`³Â½ \1NÃ0 čk 1S

30 30 ]±²` kâc ¾cÃ`Tay 1Jلč \±1¾? ³ ک½ 1

31 ³ p j³½ Âi ¾cÃ`Tay

32 32 ¾cÃ`Tay `\ =ÂGaG ¾ x?0` ¾cÃ`Tay ÇcO =ÂGaG ¾cÃ`Tay Partial-Order Planning 1½k b0 ÇcO =ÂGaG čtay Fi0 b0 \1 Fi0 ل aãb ½[ف½ 1 =ÂGaG ¾cÃ`Tay Total-Order Planning 1½k b0 =ÂGaG čtay `\ a ± Fi0 F a ± ل aãb ½[ف½ 1 ]±²` kâc ¾ ] ¾cÃ`Tay Progressive (Forward) Planner ]±²` gc ¾ ] ¾cÃ`Tay Regressive (Backward) Planner

33 33 ¾cÃ`Tay `\ =ÂGaG ¾ x?0` k ² <0`³O ]Âm³C ¾ Æh 1Jلč ÇcO =ÂGaG ¾cÃ`Tay Partial-Order Planning =ÂGaG ¾cÃ`Tay Total-Order Planning

34 34 ³NFhO 1? ¾cÃ`Tay Tay ¾1t `\ ³NFhO ďe 1W ¾1t `\ ³NFhO če 1W ¾1t `\ ¾³NFhO 1±\ 1 t±0 E 1W Ė a čtay ¾1t `\ ¾³NFhO ÇcO Tay Ė a

35 35 ÇcO =ÂGaG ¾cÃ`Tay PARTIAL-ORDER PLANNING ÇcO ¾1½Tay ª1? ª1 ¾b1i ª1 ½? č«fã`³ 0 ÇcO =ÂGaG ¾cÃ`Tay Partial-Order Planning (POP)

36 36 ÇcO =ÂGaG ¾cÃ`Tay ÇcO Tay PARTIAL-ORDER PLANNING Æh ¾0a? ĝ1½ ª1 Ğ a ¾1½1 m b0 ¾0 ³ N 1½k Actions ĊEi0 vam kâc ]?1à Ei\? : ę F [ ³ Ě ÇcO =ÂGaG ¾1½] [ k ²\ Â? ¾ x?0` ęċ] E>K 0` 1½ ª1 b0 \³p Ě ĊEi0 \a ± 0]ÂC Þ ]±³ÂC b³ ½ ª1 à b0 yam kâc ½\ =ÂGaG ¾1½] [ Ordering Constraints Þ ¾1½]±³ÂC Causal Links b1? ¾1½vamkÂC Open Preconditions Tay à ¾0cO0 ę ÇcOĚ

37 37 PARTIAL-ORDER PLANNING ÇcO =ÂGaG ¾cÃ`Tay ÇcO Tay Ã]>G ¾1½a ÇcO ¾1½Tay ¾²` a? D1 b1? vamkâc Ã? \³O³ k à b0 b1? vamkâc Ã??1ÃEi\ ¾0a? Þ ]±³ÂC à \a 1u0 ª1 à \a 1u0 ę 1 FW0 ¾1½ [0]G W _ف ¾0a?Ě 0a Ã\? E>h± ª1 à ½\ =ÂGaG ª1 à ½\ =ÂGaG Ei`\ ² 1 ¾1½Tay? «¼> ď 1 1± ¾1½Tay b0 NÃ`]G E aw Ċ]m1? ±]l± ` [0]G à 1à ]m1? F 1±Ei\ b1? vamkâc à G`³q `\ č\a =

38 38 PARTIAL-ORDER PLANNING ÇcO =ÂGaG ¾cÃ`Tay 1½ ª1 2 ak0 = 1 [ `\ Ãb1 2 E 1W Âq³G ¾0`0\ Start ª1 ~²am ª1 Start Step Ċ]±³m \1NÃ0 a Ã\ ª1 vam kâc? ª1 à ] 2a? b0 Þ ¾1½]±³ÂC Ċ\a D`³q F[ ³ ½\ =ÂGaG 1½ ª1 E O Â? 2 vam kâc = 1 [ `\ ½[ف Âq³G ¾0`0\ Finish ª1 1Ã1C ª1 Finish Step Ċ]m1? ]m?1ãei\ 2 ¾1½vamkÂC ¾ ½ Ei0 1 ±1 b Tay à Ei0 ]m?1ãei\ vam kâc à 1 a½ Ċ] ± 0\a a? 0` 2 ċ [0]G 1 0 1? 1 Q½ ² ]m1? ag >[ ª1 à ak0

39 39 SPARE TIER PROBLEM ÇcO =ÂGaG ¾cÃ`Tay ę۸ b0 ۱Ě ]Ã aã1g ¾ Æh 1Jلč

40 40 SPARE TIER PROBLEM ÇcO =ÂGaG ¾cÃ`Tay ę۸ b0 ۲Ě ]Ã aã1g ¾ Æh 1Jلč

41 41 SPARE TIER PROBLEM ÇcO =ÂGaG ¾cÃ`Tay ę۸ b0 ۳Ě ]Ã aã1g ¾ Æh 1Jلč

42 42 SPARE TIER PROBLEM ÇcO =ÂGaG ¾cÃ`Tay ę۸ b0 %Ě ]Ã aã1g ¾ Æh 1Jلč

43 43 SPARE TIER PROBLEM ÇcO =ÂGaG ¾cÃ`Tay ę۸ b0 'Ě ]Ã aã1g ¾ Æh 1Jلč

44 44 SPARE TIER PROBLEM ÇcO =ÂGaG ¾cÃ`Tay ę۸ b0 )Ě ]Ã aã1g ¾ Æh 1Jلč

45 45 SPARE TIER PROBLEM Undo ÇcO =ÂGaG ¾cÃ`Tay ę۸ b0 ۷Ě ]Ã aã1g ¾ Æh 1Jلč

46 46 SPARE TIER PROBLEM ÇcO =ÂGaG ¾cÃ`Tay ę۸ b0 ۸Ě ]Ã aã1g ¾ Æh 1Jلč

47 47 PARTIAL-ORDER PLANNING ÇcO =ÂGaG ¾cÃ`Tay ę۲ b0 ۱Ě ] >m

48 48 PARTIAL-ORDER PLANNING ÇcO =ÂGaG ¾cÃ`Tay ę۲ b0 ۲Ě ] >m

49 ³ p j³½ Âi ¾cÃ`Tay

50 50 q0 > Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, 3 rd Edition, Prentice Hall, Chapter 10