Ukuphonononga ukufunda okomeleza: Ukubumba umda olandelayo we-AI

Wamkelekile kwihlabathi eliguquguqukayo lokufunda okomeleza (RL), amandla okuguqula ahlengahlengisa ubukrelekrele bokwenziwa. I-RL iyahlukana neendlela zokufunda zemveli, inika indlela entsha apho oomatshini bangenzi nje imisebenzi kodwa bafunde kwintsebenziswano nganye. Olu hambo lokuya kwimfundo yokomeleza luya kubonisa indlela emisela ngayo imilinganiselo emitsha kubuchule be-AI bokusombulula iingxaki ezintsonkothileyo kunye nokuziqhelanisa nemingeni emitsha, efana nabantu.

Nokuba ungumfundi, unomdla, okanye uqeqeshelwe umsebenzi, sijoyine kolu hambo lunika umdla kwihlabathi lokufunda okomeleza, apho umngeni ngamnye ulithuba lokukhula kwaye amathuba okuvelisa izinto ezintsha angenasiphelo.

Inkcazo yemfundo yokomeleza

Reinforcement learning (RL) lisebe elitshintshayo nelinempembelelo yokufunda umatshini efundisa oomatshini ukwenza izigqibo ngokusebenzisana ngokuthe ngqo neendawo zabo zokuhlala. Ngokungafaniyo neendlela eziqhelekileyo ezixhomekeke kwiiseti zedatha ezinkulu okanye inkqubo esisigxina, i-RL isebenza kwindlela yokufunda yolingo kunye nempazamo. Le ndlela ivumela oomatshini ukuba bafunde kwiziphumo zezenzo zabo, ezichaphazela ngokuthe ngqo izigqibo ezilandelayo kunye nokubonisa isipili senkqubo yokufunda yendalo efana namava omntu.

I-RL yaziwa ngezinto ezininzi eziphambili ezixhasa uluhlu olubanzi losetyenziso:

• Ukufunda ngokuzimela. Ii-arhente zokufunda zokomeleza ngokuzimeleyo ziphucuka ekuhambeni kwexesha ngokwenza izigqibo, ngokujonga iziphumo, nokulungelelanisa ngokusekelwe kwimpumelelo okanye ekusileleni kwezenzo zabo. Oku kufunda kokuzimela ngundoqo ekuphuhliseni ukuziphatha okukrelekrele kwaye kuvumela iisistim ze-RL ukuba zijongane nemisebenzi efuna uhlengahlengiso olubalulekileyo.
• Ukuguquguquka kwesicelo. Ukuba bhetyebhetye kweRL kuboniswa kwiinkqubo ezahlukeneyo ezintsonkothileyo neziguquguqukayo, ukusuka kwizithuthi ezizimeleyo ezihamba kwitrafikhi ukuya kwi-algorithms yokudlala umdlalo kunye nezicwangciso zonyango lobuqu. Oku kuguquguquka kugxininisa ukusetyenziswa okubanzi kweRL kumacandelo ahlukeneyo.
• Ukufunda okuphindaphindayo kunye nokwenza ngcono. Embindini we-RL ngumjikelo oqhubekayo wolingo, impazamo, kunye nokucokisa. Le nkqubo iphindaphindwayo ibalulekile kwizicelo apho iimeko zithe gqolo ukuvela, njengokujonga iipatheni zokutshintsha kwetrafikhi okanye iimarike zemali.
• Ukudityaniswa nengxelo yabantu (RLHF). Ukuphucula iindlela zokufunda zokomelezwa kwendabuko, ukudityaniswa kwengxelo yomntu-ebizwa ngokuba yi-RLHF-yomeleza inkqubo yokufunda ngokongeza ukuqonda kwabantu. Oku kwenza iinkqubo ziphendule ngakumbi kwaye zilungelelaniswe ngcono nezinto ezikhethwa ngabantu, nto leyo exabiseke ngakumbi kwimimandla entsonkothileyo efana nokulungiswa kolwimi lwendalo.

Le intshayelelo ibeka inqanaba lokuphononongwa nzulu kwezinto kunye neendlela ze-RL, eziya kuchazwa ngokubanzi kula macandelo alandelayo. Ikunika imvelaphi ebalulekileyo efunekayo ukuze uqonde impembelelo ebanzi kunye nokubaluleka kweRL kumashishini ahlukeneyo kunye nezicelo.

Izinto zokomeleza ukufunda

Ukwakhela phezu kokuqonda kwethu okusisiseko, makhe siphonononge ezona nkalo ziphambili zichaza indlela ukomeleza ukufunda okusebenza ngayo kwiindawo ngeendawo ezahlukeneyo. Ukuqonda la macandelo kubalulekile ukubamba ukuguquguquka kunye nobunzima beenkqubo ze-RL:

• okusingqongileyo. Isetingi apho i-arhente ye-RL isebenza khona ukusuka kwimilinganiso yedijithali yorhwebo lwesitokhwe ukuya kwimeko ebonakalayo efana nokuhamba ngeedrone.
• arhente. Umenzi wesigqibo kwinkqubo ye-RL isebenzisana nokusingqongileyo kwaye yenza izigqibo ngokusekelwe kwidatha eqokelelweyo kunye neziphumo.
• inyathelo. Izigqibo ezithile okanye iintshukumo ezenziwa yi-arhente, eziphembelela ngokuthe ngqo kwiziphumo zokufunda.
• imeko. Imele imeko yangoku okanye imeko njengoko ibonwa yi-arhente. Itshintsha ngokukhawuleza njengoko i-arhente yenza, inika umxholo wokulandela izigqibo.
• Ibuyiselo. Ingxelo inikezelwa emva kwesenzo ngasinye, kunye nemivuzo eyakhayo ekhuthazayo kunye nezohlwayo eziphazamisa ukuziphatha okuthile.
• Policy. Isicwangciso okanye isethi yemithetho ekhokela izigqibo ze-arhente ngokusekelwe kwimeko yangoku, ehlanjululwe ngokufunda okuqhubekayo.
• ixabiso. Uqikelelo lwemivuzo yexesha elizayo evela kwilizwe ngalinye, nceda iarhente ibeke phambili amazwe ngenzuzo enkulu.

Izinto zokusingqongileyo, iarhente, isenzo, urhulumente, umvuzo, umgaqo-nkqubo, kunye nexabiso azizonxalenye zenkqubo; benza isakhelo esibambeneyo esivumela iiarhente zeRL ukuba zifunde kwaye zilungelelanise ngokuguquguqukayo. Esi sikhundla sokufunda ngokuqhubekekayo kwintsebenziswano ngaphakathi kokusingqongileyo sibeka uqinisekiso lokufunda ngaphandle kwezinye iindlela zokufunda zoomatshini kwaye sibonisa amandla aso amakhulu kuzo zonke izicelo ezahlukeneyo. Ukuqonda ezi elementi ngabanye kubalulekile, kodwa umsebenzi wazo odityanelweyo ngaphakathi kwenkqubo ye-RL utyhila amandla okwenyani kunye nokuguquguquka kobu buchwepheshe.

Ukubona ezi zinto zisebenza, makhe sijonge umzekelo osebenzayo kwiirobhothi zamashishini:

• okusingqongileyo. Umgca wokuhlanganisa apho ingalo yerobhothi isebenza khona. • arhente. Ingalo yerobhothi icwangciselwe ukwenza imisebenzi ethile. • inyathelo. Iintshukumo ezifana nokuchola, ukubeka, kunye nokudibanisa iindawo. • imeko. Indawo yangoku yengalo kunye nesimo somgca wendibano. • Ibuyiselo. Ingxelo ngokuchaneka nokusebenza ngempumelelo kwendibano. • Policy. Izikhokelo ezikhokela ukhetho lwerobhothi yokwandisa ukusebenza kakuhle kolandelelwano. • ixabiso. Uvavanyo lokuba zeziphi iintshukumo ezivelisa ezona ziphumo zendibano zisebenzayo ekuhambeni kwexesha.

Lo mzekelo ubonisa indlela izinto ezisisiseko zokomeleza ukufunda ezisetyenziswa ngayo kwimeko yelizwe lokwenyani, ebonisa isakhono sengalo yerobhothi yokufunda nokuziqhelanisa nonxibelelwano oluqhubekayo nokusingqongileyo. Ezo zicelo ziqaqambisa izakhono eziphambili zeesistim ze-RL kwaye zibonelela ngombono obambekayo kwithiyori exoxiwe. Njengoko siqhubeka, siya kuphonononga izicelo ezininzi kwaye singene nzulu kwizinto ezintsonkothileyo kunye namandla okuguqula ukuqinisa ukufunda, ukubonisa impembelelo yazo ebonakalayo kunye nenguqu ye-RL kwiimeko zelizwe lokwenyani.

Ukuphonononga ukusebenza kokufunda okomeleza

Ukuxabisa ngokupheleleyo impumelelo yemfundo yokomelezwa (RL) kwiinkalo ezahlukeneyo, kubalulekile ukuqonda oomatshini bayo bokusebenza. Embindini wayo, i-RL ijikeleza ekufundeni iindlela zokuziphatha ezifanelekileyo ngokusebenzisa unxibelelwano oluguquguqukayo lwezenzo, imivuzo, kunye nezohlwayo-ukwenza oko kwaziwa ngokuba yi-loop yengxelo yokuqinisa ukufunda.

Le nkqubo ibandakanya umjikelo wezenzo, ingxelo, kunye nohlengahlengiso, iyenza ibe yindlela eguquguqukayo yokufundisa koomatshini ukwenza imisebenzi ngokufanelekileyo. Nalu ucazululo lwenyathelo ngenyathelo lwendlela ukufunda okomeleza kusebenza ngayo:

• Chaza ingxaki. Chaza ngokucacileyo umsebenzi othile okanye umngeni ummeli weRL eyilelwe ukusombulula.
• Misela okusingqongileyo. Khetha umxholo apho iarhente iza kusebenza khona, enokuba luseto olwenziwe ngokwedijithali okanye imeko yelizwe lokwenyani.
• Yenza i-arhente. Yenza i-arhente ye-RL kunye nabenzi boluvo ukuqonda okungqongileyo kunye nokwenza iintshukumo.
• Qala ukufunda. Vumela i-arhente ukusebenzisana nendawo yayo, ithatha izigqibo eziphenjelelwa yinkqubo yayo yokuqala.
• Fumana ingxelo. Emva kwesenzo ngasinye, i-arhente ifumana ingxelo ngendlela yemivuzo okanye izohlwayo, ezisebenzisayo ukufunda nokulungelelanisa ukuziphatha kwayo.
• Hlaziya umgaqo-nkqubo. Hlalutya ingxelo yokuphucula izicwangciso ze-arhente, ngaloo ndlela iphucula amandla ayo okwenza izigqibo.
• Cwangcisa. Uphucula ngokuqhubekayo ukusebenza kwe-arhente ngokufunda ngokuphindaphindiweyo kunye neelophu zeengxelo.
• Sebenzisa. Ukulandela uqeqesho olwaneleyo, sebenzisa iarhente ukuba iphathe imisebenzi yelizwe lokwenyani okanye isebenze ngaphakathi kokulinganisa okuntsokothileyo.

Ukubonisa ukuba la manyathelo enkqubo asetyenziswa njani ekusebenzeni, qwalasela umzekelo we-arhente ye-RL eyilelwe ukulawula izithuthi zasedolophini:

• Chaza ingxaki. Injongo kukwandisa ukuhamba kwezithuthi kwindawo exakekileyo yedolophu ukunciphisa ixesha lokulinda kunye nokuxinana. • Misela okusingqongileyo. Inkqubo ye-RL isebenza ngaphakathi kwenethiwekhi yolawulo lwetrafikhi yendlela yokuhlangana, usebenzisa idatha yexesha langempela ukusuka kwi-traffic sensors. • Yenza i-arhente. Inkqubo yokulawula i-traffic ngokwayo, ixhotyiswe ngeenzwa kunye nabalawuli bomqondiso, isebenza njenge-arhente. • Qala ukufunda. I-ejenti iqala ukulungelelanisa amaxesha okukhanya kwe-traffic ngokweemeko zexesha langempela. • Fumana ingxelo. Kufunyenwe ingxelo entle yokunciphisa amaxesha okulinda kunye nokuxinana, ngelixa ingxelo engalunganga isenzeka xa ulibaziseko okanye imiqobo yezithuthi isanda. • Hlaziya umgaqo-nkqubo. I-arhente isebenzisa le ngxelo ukucokisa i-algorithms yayo, ikhetha awona maxesha omqondiso asebenzayo. • Cwangcisa. Inkqubo ngokuqhubekayo ilungelelanisa kwaye ifunda kwidatha eqhubekayo ukuphucula ukusebenza kakuhle kwayo. • Sebenzisa. Yakuba iqinisekisiwe ukuba iyasebenza, inkqubo iphunyezwa ngokusisigxina ukulawula i-traffic kwisiphambuka.

Izinto ezithile zendlela yeRL kulo mxholo:

• okusingqongileyo. Inkqubo yetrafikhi yendlela exakekileyo yesixeko. • arhente. Inkqubo yokulawula izithuthi exhotyiswe ngeenzwa kunye nabalawuli bomqondiso. • inyathelo. Utshintsho kumaxesha ezibane zendlela kunye nemiqondiso yabahambi ngeenyawo. • imeko. Iimeko zangoku zokuhamba kwetrafikhi, kubandakanywa inani lezithuthi, ukuxinana kwetrafikhi, kunye namaxesha omqondiso. • Ibuyiselo. Ingxelo isekelwe ekusebenzeni kwenkqubo ekucutheni amaxesha okulinda. • Nkqubo. Ii-algorithms ezandisa ixesha lomqondiso ukwandisa ukuhamba kwetrafikhi. • ixabiso. Uqikelelo malunga nefuthe lezicwangciso ezahlukeneyo zexesha kwiimeko zetrafikhi ezizayo.

Le nkqubo ye-RL iqhuba ngokuziqhelanisa nezibane zendlela ngexesha lokwenyani ukuze kunyuswe ukuhamba nokunciphisa ukuxinana okusekwe kwingxelo engagungqiyo evela kwindawo yayo. Usetyenziso olunjalo alubonisi kuphela usetyenziso olusebenzayo lwe-RL kodwa lukwaqaqambisa amandla ayo okuguquguquka kwiimeko ezinzima nezitshintshayo.

Ukuqonda i-RL ngaphakathi kwimeko ebanzi yokufunda koomatshini

Njengoko siphonononga ubunzima bokufunda okomeleza, kuyabaluleka ukuyohlula kwezinye iindlela zokufunda ngoomatshini ukuxabisa ngokupheleleyo usetyenziso kunye nemingeni eyahlukileyo. Apha ngezantsi lucazululo oluthelekisekayo lwe-RL ngokuchasene nokufunda okungagadwanga. Olu thelekiso luphuculwe ngomzekelo omtsha we-RL's application kulawulo lwegridi ehlakaniphile, egxininisa ubuninzi be-RL's kwaye igxininisa imingeni ethile ehambelana nale ndlela yokufunda.

Uhlalutyo oluthelekisayo lweendlela zokufunda koomatshini

umba	Ukufunda okubekwe esweni	Ukufunda okungalawulwa	Ukuqinisa ukufunda
Uhlobo lwedatha	Idatha ephawulweyo	Idatha engabhalwanga	Akukho datha ilungisiweyo
ingxelo	Ngqo kwaye ngoko nangoko	nanye	Ngokungathanga ngqo (imivuzo/izohlwayo)
Sebenzisa iimeko	Ukuhlelwa, ukuhlehla	Ukuphononongwa kwedatha, ukuhlanganisa	Iimeko eziguquguqukayo zokwenza izigqibo
iimpawu	Ufunda kwidathasethi eneempendulo ezaziwayo, ezilungele iziphumo ezicacileyo kunye neemeko zoqeqesho oluthe ngqo.	Ifumana iipateni ezifihlakeleyo okanye izakhiwo ngaphandle kweziphumo ezichazwe kwangaphambili, ezinkulu kuhlalutyo lokuhlola okanye ukufumana amaqela edatha.	Ufunda ngokuzama nangempazamo esebenzisa ingxelo evela kwizenzo, elungele iimeko apho izigqibo zikhokelela kwiziphumo ezahlukahlukeneyo.
imizekelo	Ukuqondwa komfanekiso, ukufunyanwa kwespam	Ukwahlulwa kwemarike, ukufunyaniswa okungaqhelekanga	Umdlalo we-AI, iimoto ezizimeleyo
mngeni	Ifuna idatasets ezinkulu ezinophawu; ayinakwenza ngokubanzi kakuhle kwidatha engabonakaliyo.	Kunzima ukuvavanya ukusebenza kwemodeli ngaphandle kwedatha ebhaliweyo.	Ukuyila inkqubo yokuvuza esebenzayo kulucelomngeni; imfuno ephezulu yokubala.

Umzekeliso wokomeleza ukufunda: Ulawulo lwegridi elumkileyo

Ukubonisa usetyenziso lwe-RL ngaphaya kweenkqubo zolawulo lwezithuthi ezihlala zixoxwa kunye nokuqinisekisa ngemizekelo eyahlukeneyo, qwalasela inkqubo yolawulo lwegridi ehlakaniphile eyenzelwe ukwandisa ukuhanjiswa kwamandla nokunciphisa inkunkuma:

• Inkcazo yengxaki. Injongo yokwandisa ukusebenza kakuhle kwamandla kuwo wonke uthungelwano lwamandla esixeko ngelixa ucutha ukucima nokunciphisa inkcitho yamandla. • Ukuseta indawo. Inkqubo ye-RL idibaniswe kwinethiwekhi yeemitha ezihlakaniphile kunye nee-router zamandla, ezihlala zibeka iliso ngexesha langempela lokusetyenziswa kwamandla kunye nokusabalalisa i-metrics. • Ukudalwa kwearhente. Umlawuli wegridi okrelekrele, oqeqeshwe ngezakhono kuhlalutyo lokuxela kwangaphambili kwaye uxhotyiselwe ukwenza ii-algorithms ze-RL ezifana ne-Q-learning okanye iindlela ze-Monte Carlo, zisebenza njenge-arhente. • Inkqubo yokufunda. I-arhente iguquguquka ngokuguquguqukayo izicwangciso zokuhambisa amandla ngokusekelwe kwiimodeli eziqikelelwayo zemfuno kunye nokubonelela. Ngokomzekelo, i-Q-learning ingaqeshwa ukucokisa ngokuthe ngcembe ezi zicwangciso ngokusebenzisa inkqubo yokuvuza evavanya ukusebenza kakuhle kokuhanjiswa kwamandla kunye nokuzinza kwegridi. • Ulwamkelo lwengxelo. Ingxelo encomekayo inikwa izenzo eziphucula uzinzo kunye nokusebenza kakuhle kwegridi, ngelixa ingxelo engalunganga ijongana nokungasebenzi kakuhle okanye ukusilela kwenkqubo, ekhokela izicwangciso zexesha elizayo ze-arhente. • Uhlaziyo lomgaqo-nkqubo. I-arhente ihlaziya izicwangciso zayo ngokusekelwe ekusebenzeni kwezenzo zangaphambili, ukufunda ukuqikelela ukuphazamiseka okunokwenzeka kunye nokulungelelanisa ukuhanjiswa ngokukhawuleza. • Ukucokiswa. Ukungena kwedatha eqhubekayo kunye nokuphindaphinda kweengxelo eziphindaphindiweyo kwenza inkqubo iphucule izicwangciso zayo zokusebenza kunye nokuchaneka kwangaphambili. • Ukuthunyelwa. Emva kokuphucula, inkqubo iphunyezwa ukulawula ngokuguquguqukayo ukuhanjiswa kwamandla kwiigridi ezininzi.

Lo mzekelo uqaqambisa indlela ukomelezwa kwemfundo enokusetyenziswa ngokufanelekileyo kwiinkqubo ezintsonkothileyo apho ukuthathwa kwezigqibo ngexesha lokwenyani kunye nokuguquguquka kubalulekile. Ikwagxininisa imingeni eqhelekileyo ekuqiniseni ukufunda, njengobunzima bokuseka imivuzo emele ngokwenene iinjongo zexesha elide kunye nokusingatha iimfuno eziphezulu zokubala zokutshintsha iimeko.

Ingxoxo ngolawulo lwegridi elumkileyo isikhokelela kuphononongo lweendlela zokufunda zokomelezwa okuphezulu kunye nokusetyenziswa kumacandelo ahlukeneyo afana nezempilo, imali, kunye neenkqubo ezizimeleyo. Ezi ngxoxo ziya kubonisa ngakumbi indlela amaqhinga e-RL alungelelanisiweyo ajongana ngayo nemingeni ethile yeshishini kunye nemiba yeenqobo ezisesikweni ezibandakanyekayo.

Inkqubela phambili yamva nje kwimfundo yokomeleza

Njengoko imfundo yokomeleza iqhubeleka nokuvela, ityhala imida yobukrelekrele bokwenziwa ngethiyori kunye nenkqubela phambili ebonakalayo. Eli candelo liqaqambisa ezi zintlu zintsha, zijolise kwizicelo ezizodwa ezibonisa indima ekhulayo ye-RL kwiinkalo ezahlukeneyo.

Ukudityaniswa nokufunda nzulu

Ukufunda ukomelezwa nzulu komeleza izakhono ze-RL zokuthatha izigqibo ngokuqondwa kwepateni ephucukileyo kufundo olunzulu. Olu hlanganiso lubalulekile kwizicelo ezifuna ukuthathwa kwezigqibo ezikhawulezileyo nezintsonkothileyo. Ibonakala ibaluleke ngakumbi kwiindawo ezifana nokujonga isithuthi esizimeleyo kunye noxilongo lwezonyango, apho ukusetyenzwa kwedatha okwexesha lokwenyani kunye nokwenza izigqibo ezichanekileyo kubalulekile kukhuseleko nokusebenza.

Ukuphumelela kunye nezicelo

Intsebenziswano phakathi kokufunda okomeleza kunye nokufunda nzulu kukhokelele kwimpumelelo ephawulekayo kumacandelo ngamacandelo, ukubonisa isakhono seRL sokuziqhelanisa nokufunda kwiinkcukacha ezinzima. Nantsi eminye imimandla ephambili apho le ndlela idityanisiweyo yenze iimpembelelo ezibalulekileyo, ebonisa ukuguquguquka kwayo kunye namandla okuguqula:

• Ukudlala umdlalo onobuchule. I-AlphaGo ye-DeepMind ngumzekelo obalaseleyo wendlela ukuqinisa ufundo olunzulu kunokoyisa imingeni enzima. Ngokuhlalutya idatha yomdlalo obanzi, i-AlphaGo iphuhlise amacebo amatsha athe ekugqibeleni agqwesa ezo ntshatsheli zehlabathi ezingabantu, ebonisa amandla okudibanisa i-RL nokufunda nzulu kwingcinga yobuchule.
• Izithuthi ezizimeleyo. Kushishino lweemoto, ukufunda okomeleza nzulu kubalulekile ekuphuculeni ukwenziwa kwezigqibo ngexesha lokwenyani. Izithuthi ezilungiselelwe ngale teknoloji zinokuhamba ngokukhuselekileyo nangokufanelekileyo ngokuziqhelanisa ngokukhawuleza nokutshintsha kweemeko zendlela kunye neenkcukacha zokusingqongileyo. Ukusetyenziswa kohlalutyo oluqikelelweyo, oluxhaswa kukufunda okunzulu, luphawula ukuqhubela phambili okubalulekileyo kubuchwepheshe beemoto, okukhokelela kwiinkqubo ezikhuselekileyo nezithembekileyo zokuqhuba ezizimeleyo.
• Isetyana. Iirobhothi ziya zikwazi ukujongana nemiceli mngeni emitsha ngenxa yokudityaniswa kokufunda okomeleza ngokufunda okunzulu. Oku kudityaniswa kubalulekile kumacandelo afana nelemveliso, apho ukuchaneka kunye nokuguquguquka kubalulekile. Njengoko iirobhothi zisebenza kwindawo eziguquguqukayo zemizi-mveliso, zifunda ukwenza ngcono iinkqubo zemveliso kunye nokuphucula ukusebenza kakuhle ngokuziqhelanisa rhoqo.
• Ukhathalelo lwempilo. Indibaniselwano ye-RL kunye nokufunda okunzulu kuguqula ukhathalelo lwesigulane ngokwenza unyango lwezonyango. Ii-algorithms zilungelelanisa izicwangciso zonyango ezisekelwe ekubekeni iliso rhoqo, ukuphucula ukuchaneka kunye nokusebenza kokungenelela kwezonyango. Le ndlela yokulungelelanisa ibaluleke kakhulu kwiimeko ezifuna uhlengahlengiso oluqhubekayo kunyango kunye nokulawulwa kwezempilo kwangaphambili.

Iimpembelelo kunye nethemba elizayo

Ngokudibanisa ukufunda okomeleza kunye nokufunda okunzulu, iisistim ezikrelekrele, eziguquguqukayo zivela ngokuzimeleyo, ziphucula kakhulu intsebenziswano yomatshini kunye nehlabathi. Ezi nkqubo ziya zisabela ngakumbi kwiimfuno zabantu kunye notshintsho lwemo engqongileyo, zibeka imigangatho emitsha yokusebenzisana kweteknoloji.

Izifundo zokomelezwa kushishino

Ukulandela uphononongo lwethu lwenkqubela phambili ebalulekileyo ekufundiseni ukomeleza, makhe sihlolisise ifuthe layo lenguqu kumacandelo ngamacandelo. Ezi meko zophononongo azibonisi nje ukuguquguquka kwe-RL kodwa zikwaqaqambisa indima yayo ekuphuculeni ukusebenza kakuhle kunye nokusombulula iingxaki ezinzima:

• Kwezemali, I-algorithms ehlakaniphile iguqula imisebenzi yemarike ngokuziqhelanisa ngokuguquguqukayo kutshintsho, ngaloo ndlela iphucula ulawulo lomngcipheko kunye nenzuzo. Ukurhweba nge-algorithmic kube sisicelo esiphambili, usebenzisa ukuqinisa ukufunda ukwenza urhwebo ngamaxesha afanelekileyo, ukwandisa ukusebenza kakuhle, kunye nokunciphisa impazamo yomntu.
• Uncedo lwezempilo olubaluleke kakhulu kwi-RL, ephucula ukhathalelo lomntu ngokuguqula ngokuguquguqukayo unyango olusekwe kwiimpendulo zesigulana ngexesha lokwenyani. Le teknoloji ingundoqo ekulawuleni iimeko ezifana nesifo sikashukela kunye nokunakekelwa kwezempilo kwangaphambili, apho inceda ukuqikelela nokuthintela imiba yempilo enokubakho.
• Kwishishini leemoto, ukufunda okomeleza kuphucula indlela ezisebenza ngayo iimoto eziziqhubayo. Iinkampani ezifana noTesla kunye noWaymo zisebenzisa le teknoloji ukuhlalutya idatha kwi-sensors zemoto ngokukhawuleza, ukunceda izithuthi ukuba zenze izigqibo ezingcono malunga nokuba zihamba phi kwaye nini ukwenza ukugcinwa. Oku akugcini nje ngokwenza iimoto zikhuseleke kodwa zikwanceda ukuba ziqhube kakuhle.
• Kwicandelo lolonwabo, I-RL ilungisa ngokutsha umdlalo ngokwenza abalinganiswa abakrelekrele abangabadlali (NPCs) abaqhelana nonxibelelwano lwabadlali. Ukongeza, iphucula iinkonzo zokusasaza kwimidiya ngokwenza iingcebiso zomxholo, ophucula ukubandakanyeka komsebenzisi ngokulungelelanisa nezinto ezikhethwa ngababukeli.
• Kwimveliso, ukufunda okomeleza kwandisa imigca yemveliso kunye nokusebenza kwekhonkco lokubonelela ngokuqikelela ukusilela okunokubakho koomatshini kunye nokucwangciswa kokugcinwa ngokubonakalayo. Olu setyenziso lunciphisa ixesha lokuphumla kwaye lwandise imveliso, lubonisa impembelelo ye-RL ekusebenzeni kakuhle kwezoshishino.
• Ulawulo lwamandla ikwabona ukuqhubela phambili nge-RL, eyenza ukusetyenziswa kwamandla ngexesha lokwenyani ngaphakathi kweegridi ezihlakaniphile. Ngokuqikelela nokufunda iipatheni zokusetyenziswa, ukomeleza ukufunda kulungelelanisa ngokufanelekileyo imfuno kunye nokubonelela, ukuphucula ukusebenza kakuhle kunye nokuzinza kweenkqubo zamandla.

Le mizekelo kuwo wonke amashishini ahlukeneyo igxininisa ukusetyenziswa okubanzi kweRL kunye nokubanakho kwayo ukuqhuba ukuveliswa kwezinto ezintsha zobuchwepheshe, ithembisa ukuqhubela phambili kunye nokwamkelwa ngokubanzi koshishino.

Ukudityaniswa kokufunda okomeleza kunye nobunye ubugcisa

Ukomelezwa kwemfundo ayikokutshintsha nje amacandelo emveli; bubuvulindlela bokumanyaniswa nobuchwephesha behlabathi, ukuqhuba izisombululo ezingaphononongwanga kunye nokuphucula ukusebenza:

• Internet Yezinto (IoT). I-RL iguqula i-IoT ngokwenza izixhobo zibe nobuchule ngexesha lokwenyani. Ngokomzekelo, iinkqubo zasekhaya ezihlakaniphile zisebenzisa i-RL ukufunda kwindlela esisebenzisana ngayo kunye neemeko ezizungezile, imisebenzi ezenzekelayo efana nokulungelelanisa izibane kunye nobushushu okanye ukuphucula ukhuseleko. Oku akugcini nje ngokugcina amandla kodwa kwenza ubomi bukhululeke ngakumbi kwaye bube lula, kubonisa indlela iRL enokuthi ngobuchule izenzele ngayo imisebenzi yethu yemihla ngemihla.
• Ubuchwepheshe beBlockchain. Kwilizwe le-blockchain, ukufunda okomeleza kunceda ekudaleni iinkqubo ezinamandla nezisebenzayo. Ingundoqo ekuphuhliseni imithetho eguquguqukayo ehambelana notshintsho kwiimfuno zenethiwekhi. Olu buchule lunokukhawulezisa ukuthengiselana kunye nokunciphisa iindleko, ukugqamisa indima ye-RL ekujonganeni neminye imingeni enkulu kwi-teknoloji ye-blockchain.
• Inyani eyongeziweyo (AR). I-RL ikwaqhubela phambili i-AR ngokwenza unxibelelwano lomsebenzisi lube lolwakho ngakumbi kwaye luphuculwe. Ilungisa umxholo wenyani ngexesha lokwenyani ngokusekwe kwindlela abasebenzisi abenza ngayo kunye nokusingqongileyo abakuyo, okwenza amava e-AR abandakanyeke ngakumbi kwaye abe yinyaniso. Oku kuluncedo ngakumbi kwiinkqubo zemfundo noqeqesho, apho i-RL-designed adaptive learning environments ikhokelela ekufundeni nasekubandakanyekeni okungcono.

Ngokudibanisa i-RL kunye neetekhnoloji ezifana ne-IoT, i-blockchain, kunye ne-AR, abaphuhlisi abaphuculi kuphela indlela yokusebenza kweenkqubo kodwa baphinde batyhale imida yento enokuthi iphunyezwe kwizicwangciso ezihlakaniphile kunye neenkqubo ezibekwe phantsi. Le ndibaniselwano ibeka inqanaba lezicelo ezizimeleyo, ezisebenzayo, kunye nezilungelelanisiweyo zetekhnoloji, zithembisa ukuqhubela phambili okunomdla kwikamva kumashishini kunye nokusetyenziswa kwetekhnoloji yemihla ngemihla.

Iikhithi zezixhobo kunye nezikhokelo zokomeleza ukufunda

Njengoko siye saphonononga usetyenziso olwahlukeneyo kunye nokudityaniswa kwethekhinoloji yokufunda ukomeleza, imfuneko yezixhobo eziphucukileyo zokuphuhlisa, ukuvavanya, kunye nokucokisa ezi nkqubo kuyacaca. Eli candelo liqaqambisa izikhokelo ezingundoqo kunye nezixhobo zokusebenza eziyimfuneko ekuyileni izisombululo ezisebenzayo ze-RL. Ezi zixhobo zilungiselelwe ukuhlangabezana neemfuno zeemeko eziguquguqukayo kunye nemingeni enzima ejongene ne-RL, ukuphucula kokubili ukusebenza kakuhle kunye nefuthe lezicelo zeRL. Makhe sijonge ngakumbi kwezinye izixhobo eziphambili eziqhubela phambili umhlaba weRL:

• Iiarhente zeTensorFlow (ii-TF-Agents). Isixhobo esinamandla ngaphakathi kwe-ecosystem ye-TensorFlow, i-TF-Agents ixhasa uluhlu olubanzi lwee-algorithms kwaye ifaneleke ngokukodwa ukudibanisa imifuziselo ephucukileyo kunye nokufunda nzulu, ukuxhasa inkqubela ekuxoxwe ngayo ngaphambili ekudityanisweni nzulu kokufunda.
• I-OpenAI Gym. Idume ngeemeko ezahlukeneyo zokulinganisa-ukusuka kwimidlalo ye-Atari yakudala ukuya kukulinganisa okuntsokothileyo komzimba-I-OpenAI Gym liqonga lokumakisha elivumela abaphuhlisi ukuba bavavanye ii-algorithms ze-RL kwiisetingi ezahlukeneyo. Kubalulekile ukuphonononga ukulungelelaniswa kwe-RL ekusetweni ngokufana nezo zisetyenziswa kulawulo lwezithuthi kunye neegridi ezihlakaniphile.
• RLlib. Isebenza kwi-Ray framework, i-RLlib ilungiselelwe i-RL ehlanjululwayo kwaye isasazwe, ukuphatha iimeko ezinzima ezibandakanya ii-arhente ezininzi, ezifana nokuvelisa kunye nokulungelelaniswa kwezithuthi ezizimeleyo.
• Imfundo yokuqinisa iPyTorch (PyTorch-RL). Isebenzisa iimpawu zekhompyutha zePyTorch ezinamandla, le seti yee-algorithms ze-RL ibonelela ngokuguquguquka okuyimfuneko kwiinkqubo ezihlengahlengisa kulwazi olutsha, olubalulekileyo kwiiprojekthi ezifuna uhlaziyo rhoqo olusekwe kwingxelo.
• Iziseko ezizinzile. Inguqulelo ephuculweyo ye-OpenAI Baselines, iBaselines eZinzileyo inikezela nge-algorithms ye-RL ebhalwe kakuhle kwaye esebenziseka lula enceda abaphuhlisi basulungekise kwaye bahlaziye iindlela ezikhoyo ze-RL, ezibalulekileyo kumacandelo afana nezempilo kunye nezezimali.

Ezi zixhobo azipheleli nje ekufezekiseni uphuhliso lwezicelo ze-RL kodwa zikwadlala indima ebalulekileyo ekuvavanyeni, ekusulungeni nasekusetyenzisweni kweemodeli kwiindawo ezahlukeneyo. Bexhobe ngokuqonda okucacileyo kwemisebenzi yabo kunye nokusetyenziswa, abaphuhlisi kunye nabaphandi banokusebenzisa ezi zixhobo ukwandisa amathuba okufunda okomeleza.

Ukusebenzisa ukulinganisa okusebenzisanayo ukuqeqesha imifuziselo yeRL

Emva kokuchaza iikhithi zezixhobo eziyimfuneko kunye nezikhokelo ezixhasa uphuhliso kunye nokucokisa iimodeli zokufunda okomeleza, kubalulekile ukugxila apho le mizekelo ivavanywa kwaye isulungekiswa khona. Iimeko zokufunda ezisebenzisanayo kunye nokulinganisa zibalulekile ekuqhubeleni phambili usetyenziso lwe-RL, ukubonelela ngoseto olukhuselekileyo nolulawulwayo olunciphisa imingcipheko yehlabathi lokwenyani.

Amaqonga okulinganisa: Imihlaba yoqeqesho eyinyani

Iiplatform ezifana ne-Unity ML-Agents kunye ne-Microsoft AirSim ayisebenzi nje njengezixhobo, kodwa njengesango lehlabathi elinenyani, elisebenzisanayo apho i-RL algorithms ifumana uqeqesho olungqongqo. La maqonga ayimfuneko kwimimandla efana nokuzimela kunye neerobhothi zasemoyeni, apho uvavanyo lwehlabathi lokwenyani luxabisa kakhulu kwaye luyingozi. Ngokulinganisa okuneenkcukacha, abaphuhlisi banokucela umngeni kwaye bacokise iimodeli ze-RL phantsi kweemeko ezahlukeneyo nezintsokothileyo, zifane ngokusondeleyo nokungacingelwa kwehlabathi lokwenyani.

Intsebenziswano enamandla ekufundeni

Ubume obuguquguqukayo beemeko zokufunda ezisebenzisanayo kuvumela imifuziselo yeRL ukuba iziqhelanise nemisebenzi kwaye iqhelane nemingeni emitsha ngexesha lokwenyani. Oku kuziqhelanisa kubalulekile kwiinkqubo zeRL ezenzelwe usetyenziso lwehlabathi lokwenyani oluguqukayo, olufana nokulawula iipotfoliyo zemali okanye ukongeza iinkqubo zetrafikhi zasedolophini.

Indima kuphuhliso oluqhubekayo kunye nokuqinisekiswa

Ngaphandle koqeqesho lokuqala, ezi meko zibalulekile kuphuculo oluqhubekayo kunye nokuqinisekiswa kwemizekelo yokufunda yokuqinisa. Banikezela ngeqonga kubaphuhlisi ukuvavanya amaqhinga amatsha kunye neemeko, ukuvavanya ukuqina kunye nokulungelelaniswa kwe-algorithms. Oku kubalulekile ekwakheni iimodeli ezinamandla ezikwaziyo ukulawula ubunzima bokwenyani behlabathi.

Ukwandisa uphando kunye nefuthe kushishino

Kubaphandi, le mimandla inciphisa i-feedback loop kuphuhliso lwemodeli, iququzelela ukuphindaphinda ngokukhawuleza kunye nokuphuculwa. Kwizicelo zorhwebo, ziqinisekisa ukuba iinkqubo ze-RL zihlolwe ngokucokisekileyo kwaye ziphuculwe ngaphambi kokuthunyelwa kwiindawo ezibalulekileyo ezifana nokunakekelwa kwezempilo kunye nemali, apho ukuchaneka nokuthembeka kubalulekile.

Ngokusebenzisa i-interactive learning and simulation environments kwinkqubo yophuhliso lwe-RL, isicelo esisebenzayo kunye nokusebenza kakuhle kwezi algorithms ezinzima ziphuculwe. Ezi qonga ziguqula ulwazi lwethiyori kusetyenziso lwehlabathi lokwenyani kunye nokuphucula ukuchaneka kunye nokusebenza kakuhle kweenkqubo zeRL, ukulungiselela indlela yokudala ubuchwephesha obukrelekrele, obuguqukayo.

Izinto eziluncedo kunye nemingeni yokufunda ukomeleza

Emva kokuphonononga iintlobo ngeentlobo zezixhobo, ukubona indlela ezisetyenziswa ngayo kwiindawo ezahlukeneyo ezifana nezempilo kunye neemoto eziziqhubayo, nokufunda malunga neekhonsepthi ezintsonkothileyo ezifana nelophu yengxelo yokuqinisa ukufunda kunye nendlela esebenza ngayo ngokufunda nzulu, ngoku siza jonga kwiinzuzo ezinkulu kunye nemingeni yokomeleza ukufunda. Le nxalenye yengxoxo yethu iya kujolisa kwindlela iRL isombulula ngayo iingxaki ezinzima kwaye ijongana nemiba yehlabathi yokwenyani, sisebenzisa oko sikufundileyo kuviwo lwethu oluneenkcukacha.

eziluncedo

• Ukusonjululwa kwengxaki entsonkothileyo. I-Reinforcement learning (RL) iyagqwesa kwiimeko ezingalindelekanga nezintsokothileyo, ezihlala ziqhuba bhetele kuneengcali zabantu. Umzekelo omkhulu nguAlphaGo, inkqubo yeRL ephumelele umdlalo wayo ngokuchasene neentshatsheli zehlabathi kumdlalo weGo. Ngaphaya kwemidlalo, iRL iye yasebenza ngokumangalisayo kwezinye iindawo. Ngokomzekelo, kulawulo lwamandla, iinkqubo ze-RL ziye zaphucula ukusebenza kakuhle kweegridi zamandla ngaphezu kokuba iingcali zicinga ukuba zinokwenzeka. Ezi ziphumo zibonisa indlela iRL enokufumana ngayo izisombululo ezitsha ngokwayo, inika amathuba anomdla kumashishini ahlukeneyo.
• Ukuziqhelanisa okuphezulu. Ukukwazi kwe-RL ukulungelelanisa ngokukhawuleza kwiimeko ezintsha kuluncedo kakhulu kwiindawo ezifana neemoto eziziqhubayo kunye nokuthengiswa kwempahla. Kule mihlaba, iinkqubo ze-RL zingatshintsha izicwangciso zazo ngokukhawuleza ukuze zitshatise iimeko ezintsha, zibonisa ukuba zibhetyebhetye kangakanani. Ngokomzekelo, ukusebenzisa i-RL ukuguqula izicwangciso zokurhweba xa utshintsho lweemarike lubonakalise ukuba lusebenza ngakumbi kuneendlela zakudala, ngakumbi ngexesha lemarike engalindelekanga.
• Ukwenza izigqibo ngokuzimeleyo. Iisistim zokomeleza ukufunda zisebenza ngokuzimeleyo ngokufunda kunxibelelwano oluthe ngqo neendawo ezihlala kuzo. Oku kuzimela kubalulekile kwiindawo ezifuna ukuthathwa kwezigqibo ngokukhawuleza, okuqhutywa yidatha, njengokuhamba ngerobhothi kunye nokhathalelo lwempilo lomntu, apho iRL ilungisa izigqibo ngokusekelwe kwidatha yesigulana eqhubekayo.
• Ukusabalala. I-algorithms ye-RL yakhelwe ukulawula ukukhula kobunzima kwaye isebenze kakuhle kwizicelo ezininzi ezahlukeneyo. Obu buchule bokulinganisa bunceda amashishini akhule kwaye aziqhelanise kwiindawo ezinjengokuthenga kwi-intanethi kunye necomputing yamafu, apho izinto zihlala zitshintsha.
• Ukufunda ngokuqhubekayo. Ngokungafaniyo nezinye iimodeli ze-AI ezinokufuna ukuphinda ziqeqeshwe, iinkqubo ze-RL zihlala zifunda kwaye ziphucula kwiintsebenziswano ezintsha, zizenza zisebenze kakhulu kumacandelo afana nokugcinwa kwangaphambili, apho ziguqula iishedyuli ngokusekelwe kwidatha yexesha langempela.

mngeni

• Ubunzulu bedatha. I-RL idinga idatha eninzi kunye nokusebenzisana rhoqo, okunzima ukuyifumana kwiimvavanyo zokuqala zeemoto eziziqhubayo. Nangona ukuphuculwa kokulinganisa kunye nokwenza idatha yokwenziwa kusinika iiseti zedatha zoqeqesho ezingcono, ukufumana idatha yomgangatho ophezulu wehlabathi lokwenene kusengumngeni omkhulu.
• Ubunzima behlabathi lokwenyani. Impendulo engalindelekanga kunye necothayo kwiisetingi zokwenyani yenza uqeqesho lwe-RL imifuziselo lubenzima. Ii-algorithms ezintsha ziyaphucula indlela ezi modeli zijongana ngayo nokulibaziseka, kodwa ukuziqhelanisa nokungacingeleki kweemeko zehlabathi lokwenyani kusengumngeni onzima.
• Ubunzima boyilo lomvuzo. Kulucelomngeni ukwenza iinkqubo zokuvuza ezilungelelanisa izenzo ezikhawulezileyo kunye neenjongo zexesha elide. Iinzame ezifana nokuphuhlisa iindlela zokufundisa zokomelezwa zibalulekile, kodwa azikasombululi ncam izinto ezintsonkothileyo kusetyenziso lwehlabathi lokwenyani.
• Iimfuno eziphezulu zokubala. I-algorithms ye-RL ifuna amandla amaninzi ekhompyutheni, ngakumbi xa isetyenziswe kwiimeko ezinkulu okanye ezinzima. Nangona kukho iinzame zokwenza ezi zixhobo zisebenze ngakumbi kwaye zisebenzise i-hardware yekhompyutha enamandla njenge-Graphics Processing Units (GPUs) kunye ne-Tensor Processing Units (TPUs), iindleko kunye nenani lezibonelelo ezifunekayo zisenokuphakama kakhulu kwimibutho emininzi.
• Ukusebenza kwesampuli. Ukufunda ukomeleza kudla ngokufuna idatha eninzi ukuze isebenze kakuhle, okuyingxaki enkulu kwimimandla efana nerobhothi okanye ukhathalelo lwempilo apho ukuqokelela idatha kungabiza okanye kuyingozi. Nangona kunjalo, iindlela ezintsha zokufunda ngaphandle komgaqo-nkqubo kunye nokufunda ibhetshi yokuqinisa zenza kube lula ukufunda ngakumbi kwiidatha ezincinci. Ngaphandle kolu phuculo, kusengumngeni ukufumana iziphumo ezilunge ngenene ngamanqaku edatha ambalwa.

Izikhokelo zexesha elizayo kunye neminye imingeni

Njengoko sijonge kwikamva, ukufunda ukomeleza kukulungele ukujongana nemingeni ekhoyo nokwandisa izicelo zayo. Nazi ezinye iinkqubela phambili ezithile kunye nendlela ekulindeleke ukuba zihlangabezane ngayo nale mingeni:

• Imiba yobungakanani. Ngelixa i-RL iyakaleka ngokwendalo, kusafuneka ilawule indawo ezinkulu nezintsokothileyo ngokufanelekileyo. Ukwenziwa kwezinto ezintsha kwiinkqubo zee-arhente ezininzi kulindeleke ukuba kuphuculwe ukuhanjiswa kwemisebenzi yokubala, enokuthi inciphise kakhulu iindleko kwaye iphucule ukusebenza ngexesha lamaxesha aphakamileyo, njengakwixesha lokwenyani lolawulo lwetrafikhi kwidolophu yonke okanye amaxesha omthwalo omkhulu kwicomputing yamafu.
• Ukuntsonkotha kosetyenziso lwehlabathi lokwenyani. Ukuvala umsantsa phakathi kokusingqongileyo okulawulwayo kunye nokungacingelwa kobomi bokwenyani kuhlala kungumba ophambili. Uphando lujolise ekuphuhliseni i-algorithms enamandla ekwazi ukusebenza phantsi kweemeko ezahlukeneyo. Umzekelo, iindlela zokufunda eziguquguqukayo, ezivavanyiweyo kwiiprojekthi zokulinga ukuhamba ngokuzimeleyo kwiimeko zemozulu eziguquguqukayo, zilungiselela i-RL ukusingatha izinto ezintsonkothileyo zokwenyani ezifanayo ngempumelelo.
• Uyilo lwenkqubo yomvuzo. Ukuyila iinkqubo zokuvuza ezilungelelanisa izenzo zexesha elifutshane kunye neenjongo zexesha elide kuyaqhubeka kungumngeni. Iinzame zokucacisa kunye nokwenza lula i-algorithms kuya kunceda ukudala imizekelo ekulula ukuyitolika kunye nokulungelelanisa kunye neenjongo zombutho, ngokukodwa kwizemali kunye nokhathalelo lwempilo, apho iziphumo ezichanekileyo zibaluleke kakhulu.
• Indibaniselwano yexesha elizayo kunye nophuhliso. Ukudityaniswa kwe-RL kunye nobuchwepheshe be-AI obuphambili obufana nothungelwano oluvelisayo lwe-adversarial (GANs) kunye nokusetyenzwa kolwimi lwendalo (NLP) kulindeleke ukuba kuphucule kakhulu amandla e-RL. Le synergy ijolise ekusebenziseni amandla etekhnoloji nganye ukukhulisa ukuguquguquka kwe-RL kunye nokusebenza kakuhle, ngakumbi kwiimeko ezinzima. Olu phuhliso lusetelwe ukwazisa usetyenziso olunamandla ngakumbi kunye nehlabathi jikelele kumacandelo awohlukeneyo.

Ngohlalutyo lwethu oluneenkcukacha, kucacile ukuba ngelixa iRL ibonelela ngamandla amakhulu okuguqula amacandelo ahlukeneyo, impumelelo yayo ixhomekeke ekoyiseni imiceli mngeni emikhulu. Ngokuqonda ngokupheleleyo amandla kunye nobuthathaka be-RL, abaphuhlisi, kunye nabaphandi banokusebenzisa ngokufanelekileyo le teknoloji ukuze baqhube izinto ezintsha kunye nokusombulula iingxaki ezinzima kwihlabathi lenene.

Iingqwalaselo zokuziphatha ekufundiseni ukomeleza

Njengoko sigqibezela uphononongo lwethu olubanzi lokomeleza ukufunda, kubalulekile ukulungisa iimpembelelo zayo zeenqobo ezisesikweni-umba wokugqibela kodwa obalulekileyo wokusasaza iinkqubo ze-RL kwiimeko zokwenyani zehlabathi. Makhe sixoxe ngoxanduva olubalulekileyo kunye nemingeni evela ngokudityaniswa kwe-RL kwitekhnoloji yemihla ngemihla, iqaqambisa imfuno yokuqwalaselwa ngenyameko kwesicelo sayo:

• Ukuzenzela izigqibo. Ukomeleza ukufunda kwenza ukuba iinkqubo zikwazi ukwenza izigqibo ezizimeleyo, ezinokuchaphazela kakhulu ukhuseleko kunye nokuphila kakuhle kwabantu. Ngokomzekelo, kwiimoto ezizimeleyo, izigqibo ezenziwe yi-RL algorithms zichaphazela ngokuthe ngqo ukhuseleko lwabakhweli kunye nabahamba ngeenyawo. Kubalulekile ukuqinisekisa ukuba ezi zigqibo azenzakalisi mntu ngamnye kwaye kukho iindlela ezomeleleyo zokusilela kwenkqubo.
• Iingxaki zabucala. Iisistim ze-RL zihlala ziqhuba izixa ezikhulu zedatha, ukuquka iinkcukacha zobuqu. Ukhuseleko lwabucala olungqongqo kufuneka luphunyezwe ukuze kuqinisekiswe ukuba ukuphathwa kwedatha kulandela imigangatho yomthetho neyeenqobo ezisesikweni, ngakumbi xa iisistim zisebenza kwiindawo zobuqu ezinje ngamakhaya okanye kwizixhobo zobuqu.
• Umkhethe kunye nobulungisa. Ukunqanda i-bias ngumceli mngeni omkhulu kusetyenziso lwe-RL. Kuba ezi nkqubo zifunda kwiindawo ezihlala kuzo, ukuthath' icala kwidatha kunokukhokelela kwizigqibo ezingafanelekanga. Lo mba ubaluleke kakhulu kwizicelo ezifana nobupolisa obuxelwe kwangaphambili okanye ukuqesha, apho iialgorithms zomkhethe zinokubethelela intswela-bulungisa ekhoyo. Abaphuhlisi kufuneka basebenzise iindlela zokungakhethi cala kwaye basoloko bevavanya ubulungisa beenkqubo zabo.
• Uxanduva lokuphendula. Ukunciphisa le mingcipheko, kufuneka kubekho izikhokelo ezicacileyo kunye neeprothokholi zeendlela zokufundisa ezomelezwa ngokuziphatha. Abaphuhlisi kunye nemibutho kufuneka bacace malunga nendlela iinkqubo zabo zeRL ezenza ngayo izigqibo, idatha abayisebenzisayo, kunye namanyathelo athathiweyo ukujongana neenkxalabo zokuziphatha. Ngaphaya koko, kufuneka kubekho iindlela zokuphendula kunye neenketho zoncedo ukuba inkqubo yeRL yenza umonakalo.
• Uphuhliso lweenqobo ezisesikweni noqeqesho: Ngexesha lophuhliso kunye nenqanaba loqeqesho, kuyafuneka ukuba kuthathelwe ingqalelo ukufunwa kwedatha kunye nokubandakanya uluhlu olwahlukileyo lwemibono. Le ndlela inceda ukujongana nokungakhethi cala okunokwenzeka kwaye iqinisekise ukuba iinkqubo ze-RL zomelele kwaye zilungile kuzo zonke iimeko zosetyenziso ezahlukeneyo.
• Impembelelo emsebenzini. Njengoko iinkqubo zeRL zisetyenziswa kakhulu kumashishini ahlukeneyo, kubalulekile ukujonga ukuba ziyichaphazela njani imisebenzi. Abantu abaphetheyo kufuneka bacinge kwaye banciphise naziphi na iziphumo ezibi kwimisebenzi, njengabantu abaphulukana nemisebenzi yabo okanye iindima zomsebenzi eziguqukayo. Kufuneka baqinisekise ukuba njengoko imisebenzi emininzi izenzela, kukho iinkqubo zokufundisa izakhono ezitsha nokudala imisebenzi kumacandelo amatsha.

Ngohlalutyo lwethu oluneenkcukacha, kucacile ukuba ngelixa iRL ibonelela ngamandla amangalisayo okuguqula amacandelo ahlukeneyo, uqwalaselo ngononophelo lwale milinganiselo yokuziphatha ibalulekile. Ngokuqaphela kunye nokujongana nale ngqwalasela, abaphuhlisi kunye nabaphandi banokuqinisekisa ukuba iteknoloji yeRL iqhubela phambili ngendlela ehambelana nezithethe kunye nemilinganiselo yoluntu.

isiphelo

Ukuntywila kwethu ngokunzulu kwimfundo yokuqinisa (RL) kusibonisile amandla ayo anamandla okuguqula amacandelo amaninzi ngoomatshini bokufundisa ukufunda nokwenza izigqibo ngenkqubo yokulinga kunye neempazamo. Ukuguquguquka kwe-RL kunye nokukwazi ukugcina ukuphucula kuyenza ibe lukhetho olubalaseleyo lokuphucula yonke into ukusuka kwiimoto eziziqhubayo ukuya kwiinkqubo zempilo. Nangona kunjalo, njengoko iRL isiba yinxalenye enkulu yobomi bethu bemihla ngemihla, kufuneka sithathele ingqalelo nzulu iimpembelelo zayo ezisesikweni. Kubalulekile ukugxila kubulungisa, ubumfihlo, kunye nokuvuleleka njengoko sijonga izibonelelo kunye nemiceli mngeni yobu buchwepheshe. Kwakhona, njengoko iRL itshintsha imarike yemisebenzi, kubalulekile ukuxhasa utshintsho olunceda abantu baphuhlise izakhono ezitsha nokudala imisebenzi emitsha. Xa sijonge phambili, akufuneki sijolise nje ekuphuculeni ubuchwepheshe beRL kodwa sikwaqinisekisa ukuba siyahlangabezana nemigangatho ephezulu yokuziphatha enceda uluntu. Ngokudibanisa izinto ezintsha kunye noxanduva, sinokusebenzisa i-RL kungekhona nje ukwenza inkqubela phambili yobugcisa kodwa nokukhuthaza utshintsho oluhle kuluntu. Oku kuqukumbela uphononongo lwethu olunzulu, kodwa sisiqalo nje sokusebenzisa iRL ngokuziphendulela ukwakha ikamva elikrelekrele nelilungileyo.