Sutton "Reinforcement Learning" 2nd Edition Ch7: n-step Bootstrapping

4VUUPO3FJOGPSDFNFOU-FBSOJOH OEFEJUJPO ྠಡձ  $IOTUFQ#PPUTUSBQQJOH ,PTVLF.JZPTIJ WFSTJPO

໨࣍ w 1SFEJDUJPO w OTUFQ5%1SFEJDUJPO w &SSPSSFEVDUJPOQSPQFSUZ w 3BOEPN8BML w
$POUSPM"MHPSJUINT w OTUFQ4BSTB w OTUFQ&YQFDUFE4BSTB w OTUFQ0⒎QPMJDZ-FBSOJOH w 1FSEFDJTJPO.FUIPETXJUI$POUSPM7BSJBUFT w 5IFOTUFQ5SFF#BDLVQ"MHPSJUIN w "6OJGZJOH"MHPSJUINOTUFQ2 М

1SFEJDUJPO

4U "U 3U Rt+1 + γVt (St+1) Rt+1 +
γRt+2 + γ2Rt+3 + ⋯ + γT−t−1RT 4U 3U 3U 35 தؒͷ৔߹ʁ

4U "U 3U 4U

OTUFQ5%QSFEJDUJPO Gt ≐ Rt+1 + γRt+2 + γ2Rt+3 + ⋯
+ γT−t−1RT Gt:t+1 ≐ Rt+1 + γVt (St+1) Gt:t+2 ≐ Rt+1 + γRt+2 + γ2Vt+1 (St+2) Gt:t+n ≐ Rt+1 + γRt+2 + ⋯ + γn−1Rt+n + γnVt+n−1 (St+n) TUFQ5% TUFQ5% OTUFQ5% .POUF$BSMP

Vt+n (St) ≐ Vt+n−1 (St) + α [Gt:t+n − Vt+n−1
(St)] OTUFQ5%QSFEJDUJPO Gt:t+n ≐ Rt+1 + γRt+2 + ⋯ + γn−1Rt+n + γnVt+n−1 (St+n)

max s π [Gt:t+n |St = s] − vπ (s)
≤ γn max s Vt+n−1 (s) − vπ (s) Gt:t+n ≐ Rt+1 + γRt+2 + ⋯ + γn−1Rt+n + γnVt+n−1 (St+n) OTUFQใु࿨ͱਅͷ7ͷؒͷޡࠩͷ࠷େ஋ 7ͱਅͷ7ͷؒͷޡࠩͷ࠷େ஋ &SSPSSFEVDUJPOQSPQFSUZ 7К 7 T T T T

$ % & Gt:t+1 ≐ Rt+1 + γVt (St+1)
Gt:t+2 ≐ Rt+1 + γRt+2 + γ2Vt+1 (St+2) TUFQͳΒ&͚ͩΛ7 & ʹ TUFQͳΒ% &Λ7 % 7 & ʹ 3BOEPN8BML w 7 " d7 & ͷॳظ஋Λ͔Β։࢝ w $͔Β։࢝ͯ͠ɺ$%&ͱҠಈͯ͠ӈʹҠಈͯ͠3FXBSE  Λಘͨͱ͢Δ w ЍͰߟ͑ͨ࣌

TUBSU ʜ ʜ
TUBUFT

$POUSPM"MHPSJUINT

OTUFQ4BSTB Gt:t+n ≐ Rt+1 + γRt+2 + ⋯ + γn−1Rt+n
+ γnQt+n−1 (St+n , At+n) Qt+n (St , At) ≐ Qt+n−1 (St , At) + α [Gt:t+n − Qt+n−1 (St , At)]

௨ͬͨύε TUFQ4BSTBͰ  ߋ৽͞ΕΔߦಈՁ஋ TUFQ4BSTBͰ  ߋ৽͞ΕΔߦಈՁ஋

OTUFQ&YQFDUFE4BSTB Gt:t+n ≐ Rt+1 + ⋯ + γn−1Rt+n + γnQt+n−1
(St+n , At+n) Gt:t+n ≐ Rt+1 + ⋯ + γn−1Rt+n + γn ∑ a π(a|st+n )Qt+n−1 (st+n , a) BDUJPO OTUFQ4BSTB OTUFQ&YQFDUFE4BSTB

OTUFQ0⒎QPMJDZ-FBSOJOH Vt+n (St) ≐ Vt+n−1 (St) + αρt:t+n−1 [Gt:t+n −
Vt+n−1 (St)] ρt:h ≐ min(h,T−1) ∏ k=t π (Ak |Sk) b (Ak |Sk) Qt+n (St , At) ≐ Qt+n−1 (St , At) + αρt+1:t+n [Gt:t+n − Qt+n−1 (St , At)] 7 2ͷਪఆͷର৅ͷ1PMJDZ  ྫ(SFFEZ ࣮ࡍʹ"DUJPOΛൃߦ͢Δ1PMJDZ  ྫЏ(SFFEZ

1FSEFDJTJPO.FUIPET  XJUI$POUSPM7BSJBUFT Gt:h = Rt+1 + γGt+1:h Gt:h ≐ ρt
(Rt+1 + γGt+1:h) Gh:h ≐ Vh−1 (Sh) ρt = π (At |St) b (At |St) ઴Խࣜͷܗʹ͢Δͱ Gt:t+n ≐ Rt+1 + γRt+2 + ⋯ + γn−1Rt+n + γnVt+n−1 (St+n) P⒎QPMJDZ Кʹͯ"UΛऔΔ֬཰͕ͩͱЛU΋ 7ͷਪఆ஋ͷόϦΞϯε͕  େ͖͘ͳΔ

ЛU͕ͷ࣌ɺαϯϓϧ͸ࣺͯΒΕΔɻ 7ͷมԽ͸ى͜Βͳ͍ͷ͕ਖ਼͍͠  ্ͷ࣌λʔήοτ͕7 4U ʹͳ͍ͬͯΔͷͰ0, Gt:h ≐ ρt (Rt+1 +
γGt+1:h) + (1 − ρt) Vh−1 (St) Кʹͯ"UΛऔΔ֬཰͕ͩͬͨ৔߹ЛU͸ Vt+n (St) ≐ Vt+n−1 (St) + α [Gt:t+n − Vt+n−1 (St)]

1FSEFDJTJPO.FUIPET  XJUI$POUSPM7BSJBUFT Gt:h ≐ Rt+1 + γ (ρt+1 Gt+1:h +
Vh−1 (St+1) − ρt+1 Qh−1 (St+1 , At+1)) = Rt+1 + γρt+1 (Gt+1:h − Qh−1 (St+1 , At+1)) + γVh−1 (St+1) Qt+n (St , At) ≐ Qt+n−1 (St , At) + α [Gt:t+n − Qt+n−1 (St , At)] Vt (s) ≐ ∑ a π(a|s)Qt (s, a) ߦಈՁ஋ͷ৔߹ Gh:h ≐ Qh−1 (Sh , Ah)

0⒎QPMJDZ-FBSOJOHXJUIPVU  *NQPSUBODF4BNQMJOH 5IFOTUFQ5SFF#BDLVQ"MHPSJUIN औΒͳ͔ͬͨ"DUJPO औͬͨ"DUJPO

5IFOTUFQ5SFF#BDLVQ"MHPSJUIN Gt:t+1 ≐ Rt+1 + γ∑ a π (a|St+1) Qt
(St+1 , a) 4UFQ 4UFQͷ৔߹͸௨ৗͷ&YQFDUFE4BSTB

5IFOTUFQ5SFF#BDLVQ"MHPSJUIN Gt:t+1 ≐ Rt+1 + γ∑ a π (a|St+1) Qt
(St+1 , a) Gt:t+2 ≐ Rt+1 + γ ∑ a≠At+1 π (a|St+1) Qt+1 (St+1 , a) +γπ (At+1 |St+1) ( Rt+2 + γ∑ a π (a|St+2) Qt+1 (St+2 , a) ) = Rt+1 + γ ∑ a≠At+1 π (a|St+1) Qt+1 (St+1 , a) + γπ (At+1 |St+1) Gt+1:t+2 4UFQ 4UFQ औΒͳ͔ͬͨ"DUJPO औͬͨ"DUJPO ઴Խࣜ

Gt:t+n ≐ Rt+1 + γ ∑ a≠At+1 π (a|St+1) Qt+n−1
(St+1 , a) + γπ (At+1 |St+1) Gt+1:t+n O4UFQ5SFF#BDLVQ"MHPSJUIN 5IFOTUFQ5SFF#BDLVQ"MHPSJUIN औΒͳ͔ͬͨ"DUJPO औͬͨ"DUJPO Qt+n (St , At) ≐ Qt+n−1 (St , At) + α [Gt:t+n − Qt+n−1 (St , At)] 6QEBUF

"6OJGZJOH"MHPSJUIN  OTUFQ2 М М͸֬཰ม਺ͰМͳΒ4BNQMF МͳΒશΞΫγϣϯͰظ଴஋

"6OJGZJOH"MHPSJUIN  OTUFQ2 М Gt:h = Rt+1 + γ ∑ a≠At+1
π (a|St+1) Qh−1 (St+1 , a) + γπ (At+1 |St+1) Gt+1:h = Rt+1 + γVh−1 (St+1) − γπ (At+1 |St+1) Qh−1 (St+1 , At+1) + γπ (At+1 |St+1) Gt+1:h = Rt+1 + γπ (At+1 |St+1) (Gt+1:h − Qh−1 (St+1 , At+1)) + γVh−1 (St+1) OTUFQ5SFF#BDLVQ $POUSPM7BSJBUF4BSTBͷЛΛК " 4 ʹม͑ͨ΋ͷ Gt:h ≐ Rt+1 + γ (σt+1 ρt+1 + (1 − σt+1) π (At+1 |St+1)) (Gt+1:h − Qh−1 (St+1 , At+1)) +γVh−1 (St+1) OTUFQ2 М $POUSPM7BSJBUF4BSTBͱOTUFQ5SFF#BDLVQΛМͰεΠον͍ͯ͠Δ

·ͱΊ w .POUF$BMSPͱPOFTUFQ5%ͷத͕ؒOTUFQ5% w தؒͷO͸྆ۃ୺ͷ৔߹ΑΓ΋Ұൠʹྑ͍݁Ռ w ࿈ଓλεΫʹ΋ΤϐιʔυλεΫʹ΋྆ํద༻Մೳ w ܭࢉίετ͸POFTUFQΑΓ΋͔͔Δ w
࠷ޙͷOTUFQ෼هԱ͠ͳ͍ͱ͍͚ͳ͍ w ֶश͕OTUFQޙʹͳΒͳ͍ͱ࣮ߦͰ͖ͳ͍ w 5%ͱಉ༷ʹεςοϓ͋ͨΓͷܭࢉίετ͸খ͘͞ۉҰ w ΞϧΰϦζϜͷҰൠԽ w &SSPSSFEVDUJPOUIFPSZ 4BSTB *NQPSUBODF4BNQMJOHΛ࢖ͬͨ0⒎QPMJDZ &YQFDUFE TBSTB 5SFF#BDLVQ w શͯΛҰൠԽͨ͠OTUFQ2 М

Sutton "Reinforcement Learning" 2nd Edition Ch7: n-step Bootstrapping

Sutton "Reinforcement Learning" 2nd Edition Ch7: n-step Bootstrapping

Kosuke Miyoshi

More Decks by Kosuke Miyoshi

Other Decks in Research

Featured

Transcript

4VUUPO3FJOGPSDFNFOU-FBSOJOH OEFEJUJPO ྠಡձ  $IOTUFQ#PPUTUSBQQJOH ,PTVLF.JZPTIJ WFSTJPO

໨࣍ w 1SFEJDUJPO w OTUFQ5%1SFEJDUJPO w &SSPSSFEVDUJPOQSPQFSUZ w 3BOEPN8BML w

1SFEJDUJPO

4U "U 3U Rt+1 + γVt (St+1) Rt+1 +

4U "U 3U 4U

OTUFQ5%QSFEJDUJPO Gt ≐ Rt+1 + γRt+2 + γ2Rt+3 + ⋯

Vt+n (St) ≐ Vt+n−1 (St) + α [Gt:t+n − Vt+n−1

max s π [Gt:t+n |St = s] − vπ (s)

$ % & Gt:t+1 ≐ Rt+1 + γVt (St+1)

TUBSU ʜ ʜ

$POUSPM"MHPSJUINT

OTUFQ4BSTB Gt:t+n ≐ Rt+1 + γRt+2 + ⋯ + γn−1Rt+n

௨ͬͨύε TUFQ4BSTBͰ  ߋ৽͞ΕΔߦಈՁ஋ TUFQ4BSTBͰ  ߋ৽͞ΕΔߦಈՁ஋

OTUFQ&YQFDUFE4BSTB Gt:t+n ≐ Rt+1 + ⋯ + γn−1Rt+n + γnQt+n−1

OTUFQ0⒎QPMJDZ-FBSOJOH Vt+n (St) ≐ Vt+n−1 (St) + αρt:t+n−1 [Gt:t+n −

1FSEFDJTJPO.FUIPET  XJUI$POUSPM7BSJBUFT Gt:h = Rt+1 + γGt+1:h Gt:h ≐ ρt

Gt:h ≐ ρt (Rt+1 + γGt+1:h) ЛU͸ظ଴஋͕ͱͳΔੑ࣭Λ࣋ͭɻ Αͬͯ$POUSPM7BSJBUFΛ଍ͯ͠΋  ظ଴஋͸มΘΒͳ͍ɻ Gt:h

ЛU͕ͷ࣌ɺαϯϓϧ͸ࣺͯΒΕΔɻ 7ͷมԽ͸ى͜Βͳ͍ͷ͕ਖ਼͍͠  ্ͷ࣌λʔήοτ͕7 4U ʹͳ͍ͬͯΔͷͰ0, Gt:h ≐ ρt (Rt+1 +

1FSEFDJTJPO.FUIPET  XJUI$POUSPM7BSJBUFT Gt:h ≐ Rt+1 + γ (ρt+1 Gt+1:h +

0⒎QPMJDZ-FBSOJOHXJUIPVU  *NQPSUBODF4BNQMJOH 5IFOTUFQ5SFF#BDLVQ"MHPSJUIN औΒͳ͔ͬͨ"DUJPO औͬͨ"DUJPO

5IFOTUFQ5SFF#BDLVQ"MHPSJUIN Gt:t+1 ≐ Rt+1 + γ∑ a π (a|St+1) Qt

5IFOTUFQ5SFF#BDLVQ"MHPSJUIN Gt:t+1 ≐ Rt+1 + γ∑ a π (a|St+1) Qt

Gt:t+n ≐ Rt+1 + γ ∑ a≠At+1 π (a|St+1) Qt+n−1

"6OJGZJOH"MHPSJUIN  OTUFQ2 М М͸֬཰ม਺ͰМͳΒ4BNQMF МͳΒશΞΫγϣϯͰظ଴஋

"6OJGZJOH"MHPSJUIN  OTUFQ2 М Gt:h = Rt+1 + γ ∑ a≠At+1

·ͱΊ w .POUF$BMSPͱPOFTUFQ5%ͷத͕ؒOTUFQ5% w தؒͷO͸྆ۃ୺ͷ৔߹ΑΓ΋Ұൠʹྑ͍݁Ռ w ࿈ଓλεΫʹ΋ΤϐιʔυλεΫʹ΋྆ํద༻Մೳ w ܭࢉίετ͸POFTUFQΑΓ΋͔͔Δ w