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Reinforcement Learning from classic to DQN
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Wonseok Jung
September 13, 2018
Research
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Reinforcement Learning from classic to DQN
고전강화학습부터 DQN 까지 설명 자료 입니다.
Wonseok Jung
September 13, 2018
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Transcript
ъചणۿҗपઁ 䤯ࢳ
ъചणۿҗपणਸ߽೯ ੋҕמगಌܻ݃য়ܳझझ۽ٜ݅ӝਤೠ ѢݽٚѪѹणפ
ࣗѐ ਗࢳোҳਗ City University of New York -Baruch College Data
Science ҕ ConnexionAIোҳਗ Freelancer Data Scientist ݽفোҳࣗъചणোҳਗ Github: https://github.com/wonseokjung Facebook: https://www.facebook.com/ws.jung.798 Blog: https://wonseokjung.github.io/
1. Dynamic Programming a. Policy iteration b. Value iteration 2.
Monte Carlo method 3. Temporal-Difference Learning a. Sarsa b. Q-learning ٩۞ۨਕாۄझࣗѐ߂गಌܻ݃য়ജ҃ҳ୷ %2/ਸਊೠੋҕמगಌܻ݃য়ٜ݅ӝ ࣽࢲ
1. Dynamic Programming a. Policy iteration b. Value iteration 2.
Monte Carlo method 3. Temporal-Difference Learning a. Sarsa b. Q-learning गಌܻ݃য়ജ҃ҳ୷߂٩۞ۨਕாۄझࣗѐ %2/ਸਊೠੋҕמगಌܻ݃য়ٜ݅ӝ .PEFMGSFF .PEFMCBTFE %FFQMFBSOJOH 3- पण
1. Dynamic Programming a. Policy iteration b. Value iteration 2.
Monte Carlo method 3. Temporal-Difference Learning a. Sarsa b. Q-learning गಌܻ݃য়ജ҃ҳ୷߂٩۞ۨਕாۄझࣗѐ %2/ਸਊೠੋҕמगಌܻ݃য়ٜ݅ӝ (SJEXPSME पण
#FGPSF%FFQMFBSOJOH "GUFS%FFQMFBSOJOH 5BCVMBS *NBHF UFYU WPJDFj ജ҃ࢶఖਬ
$MBTTJD3- %FFQ-FBSOJOH Ҋъചणਃೠਬ
2MFBSOJOH $//%2/ %2/
п-FWFM4UBUFоܰӝٸޙী(FOFSBMBHFOUܳ ٜ݅ӝоয۵ ಽܻঋޙઁٜ
गಌܻ݃য়֤ޙ University of California, Berkeley ICML 2017 Curiosity-driven Exploration by
Self-supervised Prediction
IUUQTHJUIVCDPNXPOTFPLKVOH,*14@3FJOGPSDFNFOU पणܐח $PEF +VQZUFS/PUFCPPLࢳ ࢸߨݽفઁҕ ҾӘೠਵदݶѐੋਵ۽োۅࣁਃ
Markov Decision Process
3FUVSOPG&QJTPEF &QJTPEFزউ3FUVSOػ3FXBSE 5PUBM3FXBSE
%JTDPVOUFE3FUVSO %JTDPVOUFEGBDUPSоਊػ3FXBSE 5PUBM3FXBSEXJUI%JTDPVOUFE
.%1ীࢲY(SJEXPSME Grid World Environment
.%1ীࢲY(SJEXPSME 4UBUFӒܻ٘ઝ "DUJPO࢚ ೞ ઝ 3FXBSEೣ ݾ 5SBOTJUJPO1SPCBCJMJUZ %JTDPVOUGBDUPS
3FXBSE 3FXBSE 4UBUF "DUJPO Grid World Environment
4UBUFWBMVFGVODUJPO 1PMJDZܳٮܲTUBUFWBMVFGVODUJPO 4UBUFWBMVF
4UBUFWBMVFGVODUJPO 1PMJDZܳٮܲTUBUFWBMVFGVODUJPO 4UBUFWBMVF
"DUJPO7BMVFGVODUJPO 1PMJDZܳٮܲBDUJPOWBMVFGVODUJPO 4UBUFBDUJPOWBMVF
#FMMNBOFRVBUJPO "'VOEBNFOUBMQSPQFSUZPGWBMVFGVODUJPO
0QUJNBM1PMJDZܳTUBUF 7BMVFܳ୭۽ 0QUJNBMTUBUFWBMVFGVODUJPO
0QUJNBM1PMJDZܳTUBUFBDUJPO 7BMVFܳ୭۽ 0QUJNBMTUBUFBDUJPOWBMVFGVODUJPO
#FMMNBOFRVBUJPO 0QUJNBMJUZ #FMMNBOPQUJNBMJUZFRVBUJPOW
#FMMNBOFRVBUJPO 0QUJNBMJUZ #FMMNBOPQUJNBMJUZFRVBUJPOR
ܴ .%1 3FUVSO&QJTPEF 3FUVSO&QTJTPEF EJTDPVOU 4UBUFWBMVFGVODUJPO "DUJPOWBMVFGVODUJPO 0QUJNBM1PMJDZ #FMMNBO&RVBUJPO
#FMMNBOPQUJNBMFRVBUJPO #FMMNBO&RVBUJPO 0QUJNBM1PMJDZ
Dynamic Programming
ઑѤ State, Reward, Action
ઑѤ Transition Probability ژೠয
Dynamic Programming 7BMVFGVODUJPOਸࢎਊೞৈࠁա1PMJDZ ܳӝਤ೧ҳઑചदఃҊܻೡࣻ Dynamic programmingKey idea!
Dynamic programming
Y(SJEXPSMEীࢲ%ZOBNJD1SPHSBNNJOH Grid World Environment
Y(SJEXPSME 4UBUFӒܻ٘ઝ "DUJPO࢚ ೞ ઝ 3FXBSEೣ ݾ 5SBOTJUJPO1SPCBCJMJUZ %JTDPVOUGBDUPS
3FXBSE 3FXBSE അTUBUF "DUJPO Grid World Environment TUBUF TUBUF
6QEBUF3VMF #FMMNBOFRVBUJPOਸࢎਊೞৈসؘೠ 4UBUF
فઙܨ0QUJNBM7BMVFGVODUJPOT 4UBUF7BMVF #FMMNBOPQUJNBMJUZFRVBUJPOT
فઙܨ0QUJNBM7BMVFGVODUJPOT "DUJPO7BMVF #FMMNBOPQUJNBMJUZFRVBUJPOT
Dynamic Programming فઙܨ୭7BMVFGVODUJPO State-action Value function
1PMJDZ*UFSBUJPO 7BMVF*UFSBUJPO Dynamic Programming
1PMJDZJUFSBUJPO 1.Policyܳٮۄ state-valueܳ҅ೞ Policy Evaluation ؊જPolicyܳ Policy Improvement ୭1PMJDZܳ ӝਤೠفо
җ
Policy iteration- Policy Evaluation 6QEBUF3VMFਸࢎਊೞৈ&WBMVBUJPOਸೠ 7BMVFVQEBUF 1PMJDZ 5SBOTJUJPO 1SPCBCJMJUZ 3FXBSE
/FYU4UBUF FTUJNBUFEWBMVF
ݽٚTUBUFܳ7 T ਵ۽ୡӝചदఅ пTUBUFܳ6QEBUF3VMFਸࢎਊೞৈ7 T ܳসؘೠ Policy iteration- Policy
Evaluation সؘೞݴ7 T ߸ചݒਸٸসؘܳݥ Policyܳٮۄ state-valueܳ҅ೞ
Policy iteration- Improvement 1PMJDZܳٮۄ7BMVFGVODUJPOਸ҅ೠਬח؊ա 1PMJDZܳӝਤ೧ࢲ (SFFEZ1PMJDZ
Policy iteration- Improvement (SFFEZ1PMJDZਊ
1PMJDZJUFSBUJPO 1PMJDZJUFSBUJPO0QUJNBMQPMJDZܳਸٸө 1PMJDZ&WBMVBUJPOҗ1PMJDZ*NQSPWFNFOUܳ߈ࠂೠ
(SJE8PSME&OWJSPONFOU Y(SJEXPSME
Y(SJEXPSME 4UBUFӒܻ٘ઝ "DUJPO࢚ ೞ ઝ 3FXBSEೠੌٸ݃ 5SBOTJUJPO1SPCBCJMJUZ %JTDPVOUGBDUPS (SJE8PSME&OWJSPONFOU1PMJDZJUFSBUJPO
3FXBSE (PBM "DUJPO (PBM 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE 3FXBSE
(SJE8PSME&OWJSPONFOU1PMJDZJUFSBUJPO Lੌٸ ୡӝച 7L (SFFE1PMJDZ
7L (SFFE1PMJDZ L
(SJE8PSME&OWJSPONFOU1PMJDZJUFSBUJPO
7L (SFFE1PMJDZ L
(SJE8PSME&OWJSPONFOU1PMJDZJUFSBUJPO
7L (SFFE1PMJDZ LJOG
(SJE8PSME&OWJSPONFOU1PMJDZJUFSBUJPO
1PMJDZJUFSBUJPO दো
1PMJDZ*UFSBUJPO 7BMVF*UFSBUJPO Dynamic Programming
7L (SFFE1PMJDZ Lࣻ۴ೞݶ
(SJE8PSME&OWJSPONFOU7BMVFJUFSBUJPO
7BMVF*UFSBUJPO ߈ࠂೞঋח 4UBUF "DUJPO
7BMVFJUFSBUJPO दো
.PEFMহݶ पઁ۽҃ਸ೧ࠁݴജ҃җ࢚ഐਊਸ೧ঠೠ
Monte Carlo method
.POUF$BSMPNFUIPEח%ZOBNJDQSPHSBNJOHۢ ݽٚࠁܳঌҊदೞחѪইצ पઁ۽҃ਸೞݴജ҃җ࢚ഐਊਸೠ .POUF$BSMP
पઁ۽҃ਸೞݴߓחߑߨજFOWJSPONFOU ࠁоহযبपઁ۽҃ਸೞݴPQUJNBMCFIBWJPSਸܖӝ ⮚ٸޙ .POUF$BSMP
.POUF$BSMP .POUF$BSMPחFQJTPEFCZFQJTPEF۽সؘೠ ীೖ݄ࣗ٘݃झపUFSNJOBMTUBUFө оࢲসؘೠ .POUF$BSMPח҃ਸೞݴSFUVSOػTBNQMFਸਊೞৈ TUBUFBDUJPOWBMVFܳಣӐೞৈসؘೠ
(PBM .POUF$BSMP(SJE8PSME өоࠄٍ6QEBUF 4UBSU
.POUF$BSMP दো
Temporal-Difference Learning
݅ডъചणਸೡࣻחই٣যоݶӒ Ѫ5% UFNQPSBMEJGGFSFODF MFBSOJOHੌѪ 4VUUPO 5FNQPSBM%JGGFSFODF-FBSOJOH
5FNQPSBM%JGGFSFODF-FBSOJOH .POUF$BSMP %ZOBNJDQSPHSBNNJOH .POUF$BSMPۢݽ؛হ҃ਸాೞৈWBMVFܳஏೞݴ %1ۢөоঋইبррWBMVFܳFTUJNBUFೞחѪоמ
5FNQPSBM%JGGFSFODF-FBSOJOH അTUBUFীࢲBDUJPOਸࢶఖೞݴ߉ਸ3FXBSEҗ4UBUFীEJTDPVOUGBDUPSоਊػ TUBUFWBMVFܳFTUJNBUFೞݴVQEBUFೠ .POUF$BSPMPীࢲ(Uܳঌইঠসؘоמ
5% .POUF$BSMPъੋജ҃ݽ؛ਸঌޅ೧بࢎਊоמ %ZOBNJDQSPHSBNNJOHীࢲۢ0OMJOFण өӝܻঋইب ррVQEBUFооמೞӝীFQJTPEFо ݆ӡѢաDPOUJOVFೠNPEFMীࢲࢎਊೞӝજ
5%ই٣য 5FNQPSBM%JGGSFOFDF-FBSOJOH 4BSTB 2MFBSOJOH 5FNQPSBM%JGGSFOFDF-FBSOJOH4BSTB৬2MFBSOJOH߄ఔই٣যоغ 0OQPMJDZ 0GGQPMJDZ
4BSTB 2MFBSOJOH Temporal-Diffrenece Learning
4BSTB POQPMJDZߑߨਸࢎਊೞח4BSTB TUBUFWBMVFGVODUJPOनBDUJPOWBMVFGVODUJPOਸण
4BSTB UJNFTUFQীࢲTUBUF৬BDUJPOܳلࢎਊೞৈBDUJPOWBMVFܳFTUJNBUFೠ
4BSTBQTFVEPDPEF
4BSTBQTFVEPDPEF 0OQPMJDZ
4BSTBHSJEXPSME (PBM 4UBSU "U 4U
4BSTBHSJEXPSME
҃ೞঋझపࠁоহ
4BSTBHSJEXPSME
҃ਸৈ۞ߣ೧ࠁݴBDUJPOWBMVFܳসؘೠ 1PMJDZח0OQPMJDZ
4BSTB दো
4BSTB 2MFBSOJOH Temporal-Diffrenece Learning
2MFBSOJOH 2MFBSOJOHۄҊܻࠛחPGGQPMJDZ5%DPOUSPMੋ೧ъചणߊೞח҅ӝоغ 8BULJOT FYQMPSBUJPOҗFYQMPJUBUJPOਸэೠ
2MFBSOJOHQTFVEPDPEF 0GGQPMJDZ
RMFBSOJOHHSJEXPSME (PBM 4UBSU "SHNBY 4U
2MFBSOJOHHSJEXPSME
҃ೞঋझపࠁоহ
2MFBSOJOHHSJEXPSME
҃ਸৈ۞ߣ೧ࠁݴBDUJPOWBMVFܳসؘೠ 1PMJDZח0GGQPMJDZ
2MFBSOJOH दো
٩۞ۨਕாۄझࣗѐगಌܻ݃য়ജ҃ҳ୷
%FFQMFBSOJOH https://goo.gl/images/VA89CC
%FFQMFBSOJOHਵ۽ੋ೧ https://chaosmail.github.io/deeplearning/2016/10/22/intro-to-deep-learning-for-computer-vision/ ࢎਸJOQVUਵ۽߉חѪоמ೧
%FFQ3FJOGPSDFNFOU-FBSOJOH %FFQMFBSOJOH 3FJOGPSDFNFOU-FBSOJOH https://goo.gl/images/oNu5Gr
%FFQNJOE %2/ https://www.youtube.com/watch?v=V1eYniJ0Rnk %FFQMFBSOJOHਸъചणীਊೞৈ ࢎۈࠁۨܳੜೞחੋҕמਸ݅ٞ
%2/ ,FSBT CSFBLPVU ٘ࢸݺ .BJO MJCSBSZ 'VODUJPO
%2/ ,FSBT CSFBLPVU ٘ࢸݺ .BJO MJCSBSZ %2/
ജ҃ਸࠛ۞ৡ BHFOUܳࢤࢿೠ TDPSF FQJTPEF HMPCBM@TUFQܳ೧ળ ೧ળীೖࣗ٘݅ఀणਸद ݾऀࢽѐоয ജ҃ୡӝчਸоઉৡ ੌҳрزউ߄оBDUJPOਸ۽ࢶఖೡࣻ ѱೠ
ਤജ҃ୡӝчਸܻ೧ળ ܻ೧ળ۽֎ѐझషܻܳ݅ٚ .BJO
ѱզٸө҅ࣘجѱೞחXIJMFޙਸ݅ٚ SFOEFSਬޖܳഛੋೠ SFOEFSਸਬޖীٮ ۄणࣘبо׳ۄ Ӗ۽ߥझచਸೞաঀט۰ળ झచਸೞաঀט۰ળ ֎ѐTUBUF IJTUPSZ ܳਊೞৈBDUJPOਸ
ࢶఖೠ .BJO
.BJO ࢶఖೠBDUJPOਵ۽ജ҃җ࢚ഐਊೞݴജ҃ীࢲझప SFXBSE EPOF JOGPчਸ߉ח ߉झపܳदܻ೧ળ IJTUPSZীࢲখࣁѐ৬ߑӘ߉ইৡTUBUFܳࢲ OFYU@IJTUPSZ۽ࢶ R@NBYಣӐਸ҅ೞӝਤ೧ࢲഅNPEFM۽ࠗఠաৡ2
чNBYܳBHFOUBWH@R@NBYী؊ೠ ݅ডEFBEੋ҃EFBEܳ5SVF۽߄ԲҊ TUBSU@MJGFܳೞա ৈળ
.BJO ੌदр݃UBSHFUNPEFMਸVQEBUFೠ ݅ডীલਵݶEFBEGBMTF۽߄ԲҊইפݶ OFYUIJTUPSZчਸIJTUPSZо߉ח ݅ডীEPOFݶীೖࣗ٘णࠁܳӝ۾ ೞৈ۱ೠ ੌীೖࣗ٘݃ݽ؛ਸೠ
%2/ ,FSBT CSFBLPVU ٘ࢸݺ .BJO MJCSBSZ %2/
.BJO ܲইఋܻѱীࢲبਊೡࣻب۾ܻਕ٘ߧਤܳ_ ۽ೠ T B S Tܻܳۨݫݽܻীೠ ܻۨݫݽܻоदࠁ֫ইݶणਸदೠ
.BJO ੌदр݃UBSHFUNPEFMਸVQEBUFೠ ݅ডীલਵݶEFBEGBMTF۽߄ԲҊইפݶ OFYUIJTUPSZчਸIJTUPSZо߉ח ੌীೖࣗ٘݃ݽ؛ਸೠ
*NQPSU ਃೠۄ࠳۞ܻܳࠛ۞ৡ B,FSBT $//MBZFS %FOTFMBZFS PQUJNJ[FS ாۄझীࢲ٩۞ݽ؛
*NQPSU Cܻ JOQVUਵ۽ٜযয়חӝઑ 3(#ܳ(SBZ۽݅٘חۄ࠳۞ܻ SFQMBZNFNPSZ݅٘ח D5FOTPSGMPX UFOTPSGMPXCBDLFOE UFOTPSGMPX Eӝఋ
OVNQZ SBOEPN HZN PT
%2/ ,FSBT CSFBLPVU ٘ࢸݺ .BJO MJCSBSZ %2/
%2/ ↟ SFOEFSਬޖ ↟ NPEFMMPBEਬޖ ↟ TUBUFࢎૉ
↟ BDUJPOࢎૉ ↟ FQTJMPOч ↟ FQTJMPOदҗ EFDBZܳਤ ೧ ↟ FQTJMPOEFDBZTUFQ ↟ ୡӝച
%2/ ↟ ܻۨݫݽܻীࢲࡳਸߓࢎૉ ↟ णਸदೡӝળ ↟ ݽ؛۽সؘӝ
↟ EJTDPVOUGBDUPS ↟ ܻۨݫݽܻ୭ӝ ↟ झఋೡٸBDUJPOਸ۽೧חࢸ ↟ %FFQMFBSOJOHNPEFM ↟ 5BSHFUNPEFM ↟ VQEBUFUBSHFUNPEFM ↟ ୡӝച
%2/ ↟ PQUJNJ[FS ↟ 5FOTPSCPBSE ↟ ୡӝച
4BWFػݽ؛ਝܳоઉৢٸࢎਊ
%2/ ,FSBT۽٩۞ݽ؛ٜ݅ӝ $//-BZFST %FOTF-BZFS
%2/ BDUJPOਸࢶఖೞחೣࣻ QPMJDZ ৈ ӝࢲח&QTJMPOHSFFEZ അNPEFMXFJHIUܳоઉ৬ࢲUBSHFU NPEFMਝ۽সؘೞחೣࣻ
%2/ TUBUF BDUJPO SFXBSE OFYUTUBUFܻܳۨݫݽܻী೧חೣࣻ 3FQMBZ.FNPSZ
%2/ ܻۨݫݽܻীࢲࡳইৡߓ۽ݽ؛ਸणೞחೣࣻ 3FQMBZNFNPSZ
%2/ ↟ PQUJNJ[FS ↟ 5FOTPSCPBSE пীೖࣗ٘णࠁܳӝ۾ೞ חೣࣻ ୡӝച
%2/ ↟ܻܳਤೠೣࣻ ↟ ୡӝച
%2/ 0QUJNJ[FSೣࣻ ৈӝࢲח)VCFS-PTTࢎਊ https://goo.gl/images/XGsfYx
%2/ ,FSBT CSFBLPVU दো
गಌܻ݃য়ജ҃ҳ୷
)VNBO "* %FFQMFBSOJOH 3FJOGPSDFNFOU-FBSOJOH ܲبݫੋীࢲبਊоמೞ
ৈ۞ജ҃ীࢎਊ ೞ݅ജ҃ীٮܲೠъചणঌҊ્ܻਸਊ೧ঠೠ
ೠъചण 4UBUFӝ BDUJPOܰ эঌҊ્ܻਸࢎਊೞ؊ۄب %FFQMFBSOJOHNPEFM IZQFSQBSBNFUFSਸ ೞѱࢎਊ೧ঠೠ
&NVMBUPS &OWJSPONFOU Algorithm 1SPHSBNNJOH-BOHVBHF गಌܻ݃য়ࢸীਃೠ֎о
IUUQTXXXQZUIPOPSHEPXOMPBETWFSTJPO IUUQTXXXBOBDPOEBDPNEPXOMPBE"OBDPOEB IUUQTXXXUFOTPSGMPXPSHJOTUBMM5FOTPS'MPX IUUQTLFSBTJPJOTUBMMBUJPO,FSBT 1SPHSBNNJOH-BOHVBHF1ZUIPO
&NVMBUPS IUUQXXXGDFVYDPNXFCIPNFIUNM 6CVOUV TVEPBQUHFUVQEBUF TVEPBQUHFUJOTUBMMGDFVY ."$ IUUQTCSFXTIIPNFCSFXXFCTJUF 5FSNJOBMPQFOCSFXJOTUBMMGDFVY TVEPBQUHFUJOTUBMMGDFVY &NVMBUPS'$69
Environment 0QFO"*@(ZN IUUQTHJUIVCDPNPQFOBJHZN QJQJOTUBMMHZN HJUDMPOFIUUQTHJUIVCDPNPQFOBJHZNHJU DEHZN QJQJOTUBMMF 0QFO"*@(ZN 0QFO"*(ZNਸࢎਊೞݶࠁऔѱъചणपоמೞ
Environment #BTFMJOFT IUUQTHJUIVCDPNPQFOBJCBTFMJOFT QJQJOTUBMMCBTFMJOFT HJUDMPOFIUUQTHJUIVCDPNPQFOBJCBTFMJOFTHJU DECBTFMJOFT QJQJOTUBMMF 0QFO"*@#BTFMJOFT
Environment 1IJMJQ1BRVFUUF IUUQTHJUIVCDPNQQBRVFUUFHZNTVQFSNBSJP QJQJOTUBMMHZNQVMM JNQPSUHZN JNQPSUHZN@QVMM HZN@QVMMQVMM HJUIVCDPNQQBRVFUUFHZNTVQFSNBSJP FOWHZNNBLF
QQBRVFUUF4VQFS.BSJP#SPTW 4VQFS.BSJP
Algorithm DEEP Q-NETWORK "MHPSJUIN%2/
ࢸীޙઁоࢤӟݶ IUUQTHJUIVCDPNXPOTFPLKVOH,*14@3FJOGPSDFNFOUUSFF NBTUFS%2/ য়טъചणपणъਊHJUIVCীࣁೠࢸߨৢ۰֬ওणפ
%2/ਸਊೠੋҕמगಌܻ݃য়ٜ݅ӝ
Ӓܻ٘ਘ٘৬যڌѱܳө 4UBUFӒܻ٘ઝ "DUJPO࢚ ೞ ઝ 3FXBSEೣ ݾ 5SBOTJUJPO1SPCBCJMJUZ %JTDPVOUGBDUPS
3FXBSE 3FXBSE 4UBUF "DUJPO Ӓܻ٘ਘ٘৬गಌܻ݃য়ജ҃
(PBM࠺Ү (PBM 4UBSU गಌܻ݃য়חӥߊਸחݾ Ӓܻ٘ਘ٘ݾחHPBMTUBUF۽оחѪ
गಌܻ݃য়ীࢲജ҃ 4UBUFചݶ "DUJPO࢚ ೞ ઝ ׳ܻӝ BDUJPOઑ 3FXBSEখਵ۽ೡٸ3FXBSE
ٍ۽оݶ 5SBOTJUJPO1SPCBCJMJUZ %JTDPVOUGBDUPS 4UBUF "DUJPO بੋӥߊীоөтࣻ۾֫SFXBSEܳ߉ח
҅ࣘغחपಁj
ग ܻ݃য়оখਵ۽ೞঋਵ۰Ҋೞחഅ࢚ 4UBUFоCSFBLPVUࠁ؊ࠂೞҊBDUJPO݆
3FXBSEࢸ ݾ׳ࢿೞޅೞݶ दрզٸ݃ ӥߊীࢲݣযݶ ӥߊীоөਕݶ ݾীبೞݶ 1FOBMUZ #POVTSFXBSE୶о
%FFQMFBSOJOHNPEFM 7((NPEFMBOESFHVMBS࠺Ү https://goo.gl/images/eoXooC https://goo.gl/images/s8XrCK ؊Өѱऺইࠁ
ъചण SFJOGPSDFNFOUMFBSOJOH ӝୡࢸݺ߂6OJUZNMBHFOUܳਊೞৈ݅ٚജ҃ীъചणঌҊ્ܻਊ (JUIVC IUUQTHJUIVCDPNXPOTFPLKVOH 'BDFCPPL IUUQTXXXGBDFCPPLDPNXTKVOH #MPH IUUQTXPOTFPLKVOHHJUIVCJPࢿҕ
%2/ਸਊೠੋҕמगಌܻ݃য়ٜ݅ӝ दো
ۨ߰ਸܻযೞחܻ݃য়ח݅ٚറ ܲۨ߰ীࢲࢿמݒڄয0WFSGJUUJOHইקө https://goo.gl/images/6uDmqH
ъചणোҳחഝߊ೯ 3FXBSE &YQMPSBUJPO "MHPSJUIN
хࢎפ (JUIVC IUUQTHJUIVCDPNXPOTFPLKVOH 'BDFCPPL IUUQTXXXGBDFCPPLDPNXTKVOH #MPH IUUQTXPOTFPLKVOHHJUIVCJP
3FGFSFODFT 3FJOGPSDFNFOU-FBSOJOH"O*OUSPEVDUJPO3JDIBSE44VUUPOBOE"OESFX(#BSUP4FDPOE&EJUJPO JOQSPHSFTT.*51SFTT $BNCSJEHF ." IUUQTHJUIVCDPNSMDPEFSFJOGPSDFNFOUMFBSOJOHLS