Ukuhlola ukufunda kokuqinisa: Ukubumba umngcele olandelayo we-AI

Uyemukelwa emhlabeni oguquguqukayo wokufunda okuqinisayo (RL), amandla aguqulayo abumba kabusha ubuhlakani bokwenziwa. I-RL iyahlukana nezindlela zokufunda ezijwayelekile, ihlinzeka ngendlela entsha lapho imishini ingenzi nje imisebenzi kodwa ifunda ekusebenzelaneni ngakunye. Lolu hambo oluya emfundweni yokuqinisa luzobonisa ukuthi lubeka kanjani amabhentshimakhi amasha emandleni e-AI okuxazulula izinkinga eziyinkimbinkimbi futhi azivumelanise nezinselele ezintsha, njengabantu.

Kungakhathaliseki ukuthi ungumfundi, umshisekeli, noma uchwepheshe, sijoyine kulolu hambo olujabulisayo emhlabeni wonke wokuqinisa ukufunda, lapho inselele ngayinye iyithuba lokukhula futhi amathuba okuqamba amasha angenamkhawulo.

Incazelo yemfundo yokuqinisa

I-Reinforcement learning (RL) igatsha elinamandla nelinomthelela ukufunda imishini efundisa imishini ukwenza izinqumo ngokusebenzisana okuqondile nendawo yayo. Ngokungafani nezindlela ezivamile ezithembele kumasethi edatha amakhulu noma izinhlelo ezihleliwe, i-RL isebenza ngendlela yokufunda yokuhlola nephutha. Le ndlela ivumela imishini ukuthi ifunde emiphumeleni yezenzo zayo, ibe nomthelela ngokuqondile ezinqumweni ezilandelayo futhi ibonise inqubo yokufunda yemvelo efana nesipiliyoni somuntu.

I-RL yaziwa ngezici ezimbalwa ezibalulekile ezisekela ukusetshenziswa kwayo okubanzi:

• Ukufunda okuzenzakalelayo. Ama-ejenti okufunda okuqinisa athuthuka ngokuzenzakalelayo ngokuhamba kwesikhathi ngokwenza izinqumo, ngokubheka imiphumela, nokuzivumelanisa nezimo ngokusekelwe empumelelweni noma ekuhlulekeni kwezenzo zabo. Lokhu kufunda okuzishayelayo kubalulekile ekuthuthukiseni ukuziphatha okuhlakaniphile futhi kuvumela amasistimu e-RL ukuthi aphathe imisebenzi edinga ukuguquguquka okuphawulekayo.
• Ukuhlukahluka kohlelo lokusebenza. Ukuvumelana nezimo kwe-RL kukhonjiswa kumasistimu ahlukahlukene ayinkimbinkimbi naguqukayo, kusukela ezimotweni ezizimele ezizulazula ithrafikhi kuya kuma-algorithms okudlala umdlalo okuthuthukisiwe kanye nezinhlelo zokwelashwa eziqondene nawe. Lokhu kuguquguquka kugcizelela ukusebenza okubanzi kwe-RL emikhakheni ehlukene.
• Ukufunda okuphindaphindayo nokwenza kahle. Emgogodleni we-RL wumjikelezo oqhubekayo wokuzama, iphutha, nokucwengisiswa. Le nqubo ephindaphindayo ibalulekile ezinhlelweni zokusebenza lapho izimo ziguquka ngokuqhubekayo, njengokuzulazula amaphethini ethrafikhi ashintshayo noma izimakethe zezimali.
• Ukuhlanganiswa nempendulo yomuntu (RLHF). Ukuthuthukisa izindlela zokufunda zokuqinisa ezingokwesiko, ukuhlanganiswa kwempendulo yomuntu—okubizwa ngokuthi i-RLHF—kuthuthukisa inqubo yokufunda ngokwengeza imininingwane yabantu. Lokhu kwenza amasistimu aphendule kakhudlwana futhi ahambisane kangcono nokuthandwa ngabantu, okubaluleke kakhulu ezindaweni eziyinkimbinkimbi njengokucutshungulwa kolimi lwemvelo.

Lesi sethulo sibeka isiteji sokuhlola okujulile kwezakhi nezindlela ze-RL, okuzochazwa kabanzi ezigabeni ezilandelayo. Ikunikeza isizinda esibalulekile esidingekayo ukuze uqonde ithonya elibanzi nokubaluleka kwe-RL kuzo zonke izimboni nezinhlelo zokusebenza ezihlukene.

Izakhi zokuqinisa ukufunda

Sakhela ekuqondeni kwethu okuyisisekelo, ake sihlole izici ezibalulekile ezichaza ukuthi ukufunda kokuqinisa kusebenza kanjani ezindaweni ezihlukahlukene. Ukuqonda lezi zingxenye kubalulekile ukuze ubambe ukuguquguquka nobunkimbinkimbi bezinhlelo ze-RL:

• Environment. Isilungiselelo lapho umenzeli we-RL esebenza khona sisukela ezilinganisweni zedijithali zokuhweba ngamasheya kuya kuzimo ezingokoqobo ezifana nama-drones okuzulazula.
• Agent. Umenzi wesinqumo kunqubo ye-RL usebenzisana nemvelo futhi enze izinqumo ezisekelwe kudatha eqoqiwe kanye nemiphumela.
• Action. Izinqumo ezithile noma iminyakazo eyenziwa yi-ejenti, okuyiyona nomthelela ngqo emiphumeleni yokufunda.
• State. Imele isimo samanje noma isimo njengoba sibonwa umenzeli. Ishintsha ngokushintshashintshayo njengoba i-ejenti yenza, inikeza umongo wokulandela izinqumo.
• Umvuzo. Impendulo inikezwa ngemva kwesenzo ngasinye, ngemiklomelo emihle ekhuthazayo nezinhlawulo ezidumaza ukuziphatha okuthile.
• Policy. Isu noma isethi yemithetho eqondisa izinqumo ze-ejenti ngokusekelwe esimweni samanje, elicwengisiswe ngokufunda okuqhubekayo.
• Value. Izibikezelo zemiklomelo yesikhathi esizayo evela esifundeni ngasinye, zisiza umenzeli ukuthi abeke phambili izifunda ukuze azuze kakhulu.

Izakhi zemvelo, i-ejenti, isenzo, isimo, umvuzo, inqubomgomo, kanye nenani akuzona nje izingxenye zesistimu; benza uhlaka oluhlangene oluvumela ama-agent e-RL ukuthi afunde futhi azivumelanise nezimo. Leli khono lokuqhubeka nokufunda ekusebenzisaneni ngaphakathi kwendawo libeka ukufunda kokuqinisa ngaphandle kwezinye izindlela zokufunda zomshini futhi libonisa amandla ako amakhulu kuzo zonke izinhlelo zokusebenza ezihlukahlukene. Ukuqonda lezi zakhi ngazinye kubalulekile, kodwa ukusebenza kwazo ngokuhlanganyela ohlelweni lwe-RL kuveza amandla eqiniso nokuvumelana nezimo kwalobu buchwepheshe.

Ukubona lezi zakhi zisebenza, ake sihlole isibonelo esisebenzayo kumarobhothi ezimboni:

• Environment. Umugqa wokuhlanganisa lapho ingalo yerobhothi isebenza khona. • Agent. Ingalo yerobhothi ihlelelwe ukwenza imisebenzi ethile. • Action. Ukunyakaza okunjengokukha, ukubeka, nokuhlanganisa izingxenye. • State. Indawo yamanje yengalo kanye nesimo somugqa wokuhlanganisa. • Umvuzo. Impendulo ngokunemba nokusebenza kahle komsebenzi womhlangano. • Policy. Izinkombandlela eziqondisa ukukhetha kwerobhothi ukuze kuthuthukiswe ukusebenza kahle kokulandelana kokuhlanganisa. • Value. Ukuhlola ukuthi yikuphi ukunyakaza okuletha imiphumela ephumelela kakhulu yokuhlangana ngokuhamba kwesikhathi.

Lesi sibonelo sibonisa ukuthi izinto eziyisisekelo zokufunda eziqinisayo zisetshenziswa kanjani esimweni somhlaba wangempela, sibonisa ikhono lengalo yerobhothi lokufunda nokuzivumelanisa nezimo ngokusebenzisana okuqhubekayo nendawo yayo. Izicelo ezinjalo zigqamisa amakhono athuthukile wezinhlelo ze-RL futhi zinikeza umbono ongokoqobo kuthiyori okuxoxwe ngayo. Njengoba siqhubeka, sizohlola izinhlelo zokusebenza eziningi futhi sijule ebunzimeni namandla okuguqula okufunda okuqiniswayo, sibonisa umthelela wazo ongokoqobo kanye nesimo soguquko se-RL ezimeni zomhlaba wangempela.

Ukuhlola ukusebenza kokufunda okuqiniswayo

Ukuze ujabulele ngokugcwele ukusebenza ngempumelelo kokufunda okuqiniswayo (RL) emikhakheni ehlukahlukene, kubalulekile ukuqonda indlela yokusebenza kwayo. Emgogodleni wayo, i-RL igxile ekufundeni ukuziphatha okuhle ngokudlala ngokushintshashintsha kwezenzo, imiklomelo, nezinhlawulo—ukwenza lokho okwaziwa ngokuthi iluphu yempendulo yokufunda eqinisayo.

Le nqubo ihlanganisa umjikelezo wezenzo, impendulo, kanye nokulungiswa, okwenza kube indlela eguquguqukayo yemishini yokufundisa ukwenza imisebenzi ngokuphumelelayo. Nakhu ukuhlukaniswa kwesinyathelo ngesinyathelo kokuthi ukufunda kokuqinisa ngokuvamile kusebenza kanjani:

• Chaza inkinga. Khomba ngokucacile umsebenzi othile noma inselele umenzeli we-RL eklanyelwe ukuyixazulula.
• Misa imvelo. Khetha umongo lapho umenzeli azosebenza khona, okungenzeka kube isilungiselelo esilingiswa ngokwedijithali noma isimo somhlaba wangempela.
• Dala i-ejenti. Dala i-ejenti ye-RL enezinzwa ukuze uqonde indawo eyizungezile futhi wenze izenzo.
• Qala ukufunda. Vumela i-ejenti ukuthi ihlanganyele nendawo yayo, ithathe izinqumo ezithonywe ukuhlela kwayo kokuqala.
• Thola impendulo. Ngemva kwesenzo ngasinye, i-ejenti ithola impendulo ngendlela yemiklomelo noma izinhlawulo, ezisebenzisayo ukuze ifunde futhi ivumelanise ukuziphatha kwayo.
• Buyekeza inqubomgomo. Hlaziya impendulo ukuze wenze ngcono amasu e-ejenti, ngaleyo ndlela uthuthukise amakhono ayo okwenza izinqumo.
• Hlela. Qhubeka uthuthukisa ukusebenza komenzeli ngokufunda okuphindaphindayo kanye nezihibe zempendulo.
• Sebenzisa. Ngemva kokuqeqeshwa okwanele, sebenzisa i-ejenti ukuthi isingathe imisebenzi yomhlaba wangempela noma isebenze ngaphakathi kokulingisa okuyinkimbinkimbi.

Ukukhombisa ukuthi lezi zinyathelo zenqubo zisetshenziswa kanjani ekusebenzeni, cabangela isibonelo somenzeli we-RL oklanyelwe ukuphatha ithrafikhi yasemadolobheni:

• Chaza inkinga. Umgomo uwukuthuthukisa ukuhamba kwethrafikhi ezimpambanweni zedolobha eziphithizelayo ukuze kuncishiswe izikhathi zokulinda nokuminyana. • Misa imvelo. Uhlelo lwe-RL lusebenza ngaphakathi kwenethiwekhi yokulawulwa kwethrafikhi empambanweni yomgwaqo, kusetshenziswa idatha yesikhathi sangempela evela kuzinzwa zethrafikhi. • Dala i-ejenti. Uhlelo lokulawula ithrafikhi ngokwalo, olufakwe izinzwa nezilawuli zesignali, lusebenza njenge-ejenti. • Qala ukufunda. Umenzeli uqala ukulungisa izikhathi zamarobhothi ngokusekelwe ezimeni zethrafikhi yesikhathi sangempela. • Thola impendulo. Kutholwa impendulo enhle yokunciphisa izikhathi zokulinda nokuminyana, kuyilapho impendulo engemihle yenzeka lapho ukubambezeleka noma ukuvinjwa kwethrafikhi kwanda. • Buyekeza inqubomgomo. Umenzeli usebenzisa le mpendulo ukuze enze ngcono ama-algorithms ayo, ekhetha izikhathi zesignali ezisebenza kahle kakhulu. • Hlela. Isistimu ilungisa ngokuqhubekayo futhi ifunda kudatha eqhubekayo ukuze ithuthukise ukusebenza kahle kwayo. • Sebenzisa. Uma sekufakazelwe ukuthi isebenza ngempumelelo, isistimu isetshenziswa unomphela ukuphatha ithrafikhi ezimpambanweni zomgwaqo.

Izici ezithile zesistimu ye-RL kulo mongo:

• Environment. Uhlelo lwethrafikhi lwempambanomgwaqo yedolobha elimatasa. • Agent. Isistimu yokulawula ithrafikhi efakwe izinzwa nezilawuli zesignali. • Action. Izinguquko ezikhathini zamarobhothi namasiginali yabahamba ngezinyawo. • State. Izimo zamanje zokugeleza kwethrafikhi, okuhlanganisa ukubalwa kwezimoto, ukuminyana kwethrafikhi, nezikhathi zamasignali. • Umvuzo. Impendulo isekelwe ekusebenzeni kwesistimu ekwehliseni izikhathi zokulinda. • Inqubomgomo. Ama-algorithms athuthukisa isikhathi sesignali ukuthuthukisa ukuhamba kwethrafikhi. • Value. Izibikezelo mayelana nemithelela yamasu ahlukahlukene okugcina isikhathi ezimweni zethrafikhi zesikhathi esizayo.

Le sistimu ye-RL iqhubeka ijwayela amarobhothi ngesikhathi sangempela ukuze ithuthukise ukugeleza nokunciphisa ukuminyana ngokusekelwe empendulweni engaguquki evela endaweni yayo. Izinhlelo ezinjalo azibonisi nje kuphela ukusetshenziswa okungokoqobo kwe-RL kodwa futhi zigqamisa amandla ayo okuzivumelanisa nezimo eziyinkimbinkimbi nezishintshayo.

Ukuqonda i-RL ngaphakathi komongo obanzi wokufunda komshini

Njengoba sihlola ubunkimbinkimbi bokufunda kokuqinisa, kubaluleka ukukuhlukanisa kwezinye izindlela zokufunda zomshini ukuze sazise ngokugcwele ukusetshenziswa kwayo okuhlukile nezinselele. Ngezansi ukuhlaziya okuqhathanisayo kwe-RL nokufunda okungagadiwe nokungagadiwe. Lokhu kuqhathanisa kuthuthukiswa isibonelo esisha sohlelo lwe-RL ekuphathweni kwegridi ehlakaniphile, egcizelela ukuguquguquka kwe-RL futhi igqamisa izinselele ezithile ezihlobene nale ndlela yokufunda.

Ukuhlaziywa okuqhathanisayo kwezindlela zokufunda zomshini

aspect	Ukufunda okugadiwe	Ukufunda okungagadiwe	Ukuqiniswa kokufunda
Uhlobo lwedatha	Idatha enelebula	Idatha engenamalebula	Ayikho idathasethi engashintshi
Impendulo	Ngqo futhi ngokushesha	None	Okungaqondile (imiklomelo/izijeziso)
Sebenzisa amacala	Ukuhlelwa, ukwehla	Ukuhlola idatha, ukuhlanganisa	Izindawo zokwenza izinqumo ezinamandla
Izici	Ifunda kudathasethi enezimpendulo ezaziwayo, ilungele imiphumela ecacile nezimo zokuqeqesha eziqondile.	Ithola amaphethini noma izakhiwo ezifihliwe ngaphandle kwemiphumela echazwe kusengaphambili, ekahle ekuhlaziyeni kokuhlola noma ekutholeni amaqoqo edatha.	Ufunda ngokuzama nangephutha esebenzisa impendulo evela ezenzweni, elungele izindawo lapho izinqumo ziholela emiphumeleni eyahlukahlukene.
Izibonelo	Ukuqashelwa kwesithombe, ukutholwa kogaxekile	Ukuhlukaniswa kwemakethe, ukutholwa okudidayo	Umdlalo we-AI, izimoto ezizimele
Izinselele	Idinga amasethi edatha amakhulu anelebuli; ingase ingahlanganisi kahle idatha engabonakali.	Kunzima ukuhlola ukusebenza kwemodeli ngaphandle kwedatha enelebula.	Ukuklama uhlelo lokuklomelisa olusebenzayo kuyinselele; isidingo esikhulu sekhompyutha.

Umfanekiso wokufunda okuqinisayo: Ukuphathwa kwegridi ehlakaniphile

Ukuze ubonise ukusetshenziswa kwe-RL ngale kwamasistimu okuphatha ithrafikhi okuvame ukuxoxwa ngawo kanye nokuqinisekisa izibonelo ezihlukahlukene, cabangela uhlelo lokuphatha igridi ehlakaniphile eklanyelwe ukuthuthukisa ukusatshalaliswa kwamandla nokunciphisa ukumoshakala:

• Incazelo yenkinga. Khomba ukukhulisa ukusebenza kahle kwamandla kuwo wonke amagridi kagesi edolobha kuyilapho unciphisa ukucisha futhi unciphisa ukumosheka kwamandla. • Ukusethwa kwendawo. Uhlelo lwe-RL luhlanganiswe nenethiwekhi yamamitha ahlakaniphile namarutha wamandla, ahlala eqapha ukusetshenziswa kwamandla kwesikhathi sangempela kanye namamethrikhi okusabalalisa. • Ukudalwa komenzeli. Isilawuli segridi esihlakaniphile, esiqeqeshelwe amakhono kuzibalo ezibikezelayo futhi esihlonyiselwe ukwenza ama-algorithms e-RL njenge-Q-learning noma izindlela ze-Monte Carlo, sisebenza njenge-ejenti. • Inqubo yokufunda. I-ejenti ijwayela ngokuguquguqukayo amasu okusabalalisa amandla ngokusekelwe kumamodeli aqagelayo wesidingo nokunikezwa. Isibonelo, i-Q-learning ingase isetshenziswe ukuze kucwengwe kancane kancane lawa maqhinga ngohlelo lokuklomelisa oluhlola ukusebenza kahle kokusatshalaliswa kwamandla nokuzinza kwegridi. • Ukwamukela impendulo. Kunikezwa impendulo enhle ngezenzo ezithuthukisa ukuzinza nokusebenza kahle kwegridi, kuyilapho impendulo engeyinhle ibhekana nokungasebenzi kahle noma ukwehluleka kwesistimu, eqondisa amasu esikhathi esizayo omenzeli. • Ukuvuselelwa kwenqubomgomo. I-ejenti ibuyekeza amasu ayo ngokusekelwe ekusebenzeni kwezenzo zangaphambilini, ifunda ukulindela ukuphazamiseka okungenzeka futhi ilungise ukusabalalisa ngokuqhubekayo. • Ukulungiswa kabusha. Ukungena kwedatha okuqhubekayo kanye nezihibe zempendulo eziphindaphindwayo zenza isistimu ithuthukise amasu ayo okusebenza nokunemba kokubikezela. • Ukuthunyelwa. Ngemva kokuthuthukisa, isistimu isetshenziswa ukuze ilawule ngokuguquguqukayo ukusatshalaliswa kwamandla kuwo wonke amagridi amaningi.

Lesi sibonelo sigqamisa ukuthi ukufunda kokuqinisa kungasetshenziswa kanjani ezinhlelweni eziyinkimbinkimbi lapho ukuthathwa kwezinqumo ngesikhathi sangempela nokuzivumelanisa nezimo kubalulekile. Iphinde igqamise izinselelo ezijwayelekile ekuqiniseni ukufunda, njengobunzima bokusetha imiklomelo emele ngempela imigomo yesikhathi eside kanye nokusingatha izidingo eziphezulu zokubala zokushintsha izindawo.

Ingxoxo yokuphathwa kwegridi ehlakaniphile isiholela ekuhloleni amasu okufunda okuqinisa athuthukile kanye nokusetshenziswa emikhakheni eyahlukene njengokunakekelwa kwezempilo, ezezimali, nezinhlelo ezizimele. Lezi zingxoxo zizophinde zibonise ukuthi amasu e-RL enziwe ngendlela oyifisayo abhekana kanjani nezinselele ezithile zezimboni kanye nezindaba zokuziphatha ezizibandakanyayo.

Intuthuko yakamuva ekufundiseni okuqiniswayo

Njengoba ukufunda kokuqinisa kuqhubeka nokuvela, kweqa imingcele yobuhlakani bokwenziwa ngokuthuthuka okubalulekile kwethiyori kanye nokusebenza. Lesi sigaba sigqamisa lezi zinto ezintsha eziqanjiwe, ezigxile ezinhlelweni ezihlukile ezibonisa indima ekhulayo ye-RL kuzo zonke izinkambu ezihlukene.

Ukuhlanganiswa nokufunda okujulile

Ukufunda okujulile kokuqinisa kuthuthukisa amakhono e-RL okwenza izinqumo ngokubonwa kwephethini ethuthukisiwe ekufundeni okujulile. Lokhu kuhlanganiswa kubalulekile ezinhlelweni ezidinga ukuthathwa kwezinqumo okusheshayo nokuyinkimbinkimbi. Ibonakala ibalulekile ikakhulukazi ezindaweni ezifana nokuzulazula kwemoto okuzenzakalelayo kanye nokuxilongwa kwezokwelapha, lapho ukucutshungulwa kwedatha ngesikhathi sangempela kanye nokwenziwa kwezinqumo okunembile kubalulekile ekuphepheni nasekusebenzeni kahle.

Ukuthuthukiswa kanye nezicelo

Ukusebenzisana phakathi kokufunda okuqinisiwe nokufunda okujulile kuye kwaholela ekuphumeleleni okumangalisayo emikhakheni ehlukahlukene, okubonisa ikhono le-RL lokuzivumelanisa nokufunda kudatha eyinkimbinkimbi. Nazi ezinye izindawo ezibalulekile lapho le ndlela edidiyelwe ibe nomthelela omkhulu, ekhombisa ukuguquguquka kwayo kanye namandla ayo okuguqula:

• Ukudlala umdlalo wamasu. I-AlphaGo ye-DeepMind iyisibonelo esihle sokuthi ukufunda okujulile kokuqinisa kunganqoba kanjani izinselele eziyinkimbinkimbi. Ngokuhlaziya idatha eningi yokudlala, i-AlphaGo ithuthukise amasu amasha agcina edlula lawo ompetha bomhlaba babantu, ebonisa amandla okuhlanganisa i-RL nokufunda okujulile ekucabangeni kwamasu.
• Izimoto ezizimele. Embonini yezimoto, ukufunda okujulile kokuqinisa kubalulekile ekuthuthukiseni ukwenza izinqumo ngesikhathi sangempela. Izimoto ezilungiswe ngalobu buchwepheshe zingahamba ngokuphepha nangempumelelo ngokuzivumelanisa ngokushesha nezimo zethrafikhi ezishintshayo kanye nedatha yemvelo. Ukusetshenziswa kokuhlaziya okubikezelwayo, okuxhaswe ukufunda okujulile, kuphawula intuthuko ebalulekile kubuchwepheshe bezimoto, okuholela ezinhlelweni zokushayela ezizimele eziphephile nezinokwethenjelwa.
• Robotics. Amarobhothi aya ngokuya ekwazi ukubhekana nezinselele ezintsha ngenxa yokuhlanganiswa kokufunda okuqinisiwe nokufunda okujulile. Lokhu kuhlanganiswa kubalulekile emikhakheni efana neyokukhiqiza, lapho ukunemba nokuvumelana nezimo kubalulekile. Njengoba amarobhothi esebenza ezindaweni zezimboni ezinamandla, afunda ukwenza ngcono izinqubo zokukhiqiza futhi athuthukise ukusebenza kahle ngokuzivumelanisa nezimo.
• Ukunakekela impilo. Inhlanganisela ye-RL nokufunda okujulile kuguqula ukunakekelwa kwesiguli ngokwenza ukwelashwa okuqondene nawe. Ama-algorithms aguqula ngendlela eguquguqukayo izinhlelo zokwelashwa ngokusekelwe ekuqapheni okuqhubekayo, ukuthuthukisa ukunemba nokusebenza kokungenelela kwezokwelapha. Le ndlela yokuguquguquka ibaluleke kakhulu ezimeni ezidinga ukulungiswa okuqhubekayo ekwelapheni nasekulawuleni ukunakekelwa kwezempilo okubikezelayo.

Imithelela namathemba esikhathi esizayo

Ngokuhlanganisa ukufunda okuqinisayo nokufunda okujulile, amasistimu ahlakaniphile, aguquguqukayo azishintsha ngokuzenzakalelayo, athuthukisa kakhulu ukusebenzisana komshini nomhlaba. Lezi zinhlelo ziya ngokuya zisabela ezidingweni zabantu kanye nezinguquko zemvelo, zibeka izindinganiso ezintsha zokusebenzelana kobuchwepheshe.

Izibonelo zezifundo zokuqinisa embonini

Ngemva kokuhlola kwethu inqubekelaphambili ebalulekile ekufundeni kokuqinisa, ake sihlole umthelela wako wokuguqula emikhakheni eyahlukene. Lezi zibonelo zezifundo azibonisi nje kuphela ukuguquguquka kwe-RL kodwa futhi zigqamisa indima yayo ekuthuthukiseni ukusebenza kahle nokuxazulula izinkinga eziyinkimbinkimbi:

• Kwezezimali, Ama-algorithms ahlakaniphile aguqula ukusebenza kwemakethe ngokuzivumelanisa ngokuguquguqukayo nezinguquko, ngaleyo ndlela athuthukise ukuphathwa kwengozi kanye nenzuzo. Ukuhweba nge-algorithmic sekuyisicelo esibalulekile, kusetshenziswa ukufunda okuqiniswayo ukwenza ukuhweba ngezikhathi ezifanele, ukwandisa ukusebenza kahle, nokunciphisa amaphutha abantu.
• Ukunakekelwa kwezempilo kuhlomula kakhulu ku-RL, okuthuthukisa ukunakekelwa komuntu siqu ngokushintsha izindlela zokwelapha ezisuselwe ezimpendulweni zesiguli zesikhathi sangempela. Lobu buchwepheshe bubalulekile ekulawuleni izimo ezifana nesifo sikashukela kanye nokunakekelwa kwezempilo okubikezelwayo, lapho busiza khona ukulindela nokuvimbela izinkinga zempilo ezingaba khona.
• Embonini yezimoto, ukufunda kokuqinisa kuthuthukisa indlela izimoto ezizishayelayo ezisebenza ngayo. Izinkampani ezifana no-Tesla no-Waymo zisebenzisa lobu buchwepheshe ukuhlaziya idatha evela kuzinzwa zezimoto ngokushesha, zisize izimoto zenze izinqumo ezingcono mayelana nokuthi zihambe kuphi nokuthi zilungise nini. Lokhu akugcini nje ngokwenza izimoto ziphephe kodwa futhi kuzisiza ukuthi zisebenze kahle.
• Emkhakheni wezokuzijabulisa, I-RL ibumba kabusha amageyimu ngokudala izinhlamvu ezihlakaniphile ezingezona umdlali (ama-NPC) ezijwayela nokusebenzisana kwabadlali. Ukwengeza, ithuthukisa izinsiza zokusakaza bukhoma zemidiya ngokwenza izincomo zokuqukethwe kube ngokwakho, okuthuthukisa ukusebenzelana komsebenzisi ngokuqondanisa nokuthandwayo kwababukeli.
• Kwezokukhiqiza, ukufunda kokuqinisa kuthuthukisa imigqa yokukhiqiza kanye nemisebenzi ye-supply chain ngokubikezela ukwehluleka komshini okungenzeka kube khona kanye nokuhlela ukulungiswa ngokuqhubekayo. Lolu hlelo lokusebenza lunciphisa isikhathi sokuphumula futhi lukhulise ukukhiqiza, lubonisa umthelela we-RL ekusebenzeni kahle kwezimboni.
• Ukuphathwa Kwamandla futhi ibona intuthuko nge-RL, ethuthukisa ukusetshenziswa kwamandla ngesikhathi sangempela ngaphakathi kwamagridi ahlakaniphile. Ngokubikezela nokufunda amaphethini okusetshenziswa, ukuqinisa ukufunda kulinganisa ngempumelelo isidingo nokuhlinzeka, ukuthuthukisa ukusebenza kahle nokusimama kwezinhlelo zamandla.

Lezi zibonelo kuzo zonke izimboni ezihlukahlukene zigcizelela ukusebenza okubanzi kwe-RL namandla ayo okuqhuba ukuqanjwa kabusha kwezobuchwepheshe, okuthembisa ukuthuthuka okwengeziwe kanye nokwamukelwa okubanzi kwemboni.

Ukuhlanganiswa kokufunda kokuqinisa nobunye ubuchwepheshe

Ukufunda ngokuqiniswa akukona nje ukuguqula imikhakha yendabuko; isungula ukuhlanganiswa nobuchwepheshe besimanje, ukushayela izixazululo ezingakahlolisiswa kanye nokuthuthukisa ukusebenza:

• Inthanethi Things (IoT). I-RL iguqula i-IoT ngokwenza amadivayisi ahlakaniphe ngesikhathi sangempela. Isibonelo, amasistimu wasekhaya ahlakaniphile asebenzisa i-RL ukuze afunde endleleni esisebenzisana ngayo nawo nezimo eziwazungezile, ukwenza imisebenzi efana nokulungisa izibani nezinga lokushisa noma ukuthuthukisa ukuphepha. Lokhu akugcini nje ngokusindisa amandla kodwa futhi kwenza ukuphila kube ntofontofo futhi kube lula, okubonisa ukuthi i-RL ingakwazi kanjani ukwenza ngokuzenzakalelayo izinqubo zethu zansuku zonke.
• Ubuchwepheshe be-Blockchain. Emhlabeni we-blockchain, ukufunda kokuqinisa kusiza ukudala amasistimu anamandla nasebenza kahle. Kuwukhiye ekwakheni imithetho eguquguqukayo evumelana nezinguquko ezidingweni zenethiwekhi. Leli khono lingasheshisa ukuthengiselana futhi linciphise izindleko, ligqamisa indima ye-RL ekubhekaneni nezinselelo ezinkulu kubuchwepheshe be-blockchain.
• Okungokoqobo ukungathandwa kwabathelisi esikubona (AR). I-RL iphinde ithuthukise i-AR ngokwenza ukusebenzisana komsebenzisi kube okomuntu siqu futhi kuthuthukiswe. Ilungisa okuqukethwe okubonakalayo ngesikhathi sangempela ngokusekelwe endleleni abasebenzisi abenza ngayo kanye nendawo abakuyo, okwenza ukuzizwisa kwe-AR kuhehe futhi kube ngokoqobo. Lokhu kuwusizo ikakhulukazi ezinhlelweni zemfundo nokuqeqesha, lapho izindawo zokufunda eziguquguqukayo eziklanywe i-RL ziholela ekufundeni nasekuzibandakanyeni okungcono.

Ngokuhlanganisa i-RL nobuchwepheshe obufana ne-IoT, i-blockchain, ne-AR, abathuthukisi abathuthukisi nje kuphela indlela amasistimu asebenza ngayo kodwa futhi bacindezela imikhawulo yalokho okungazuzwa kuzilungiselelo ezihlakaniphile nezinhlelo ezihlukaniselwe izindawo. Le nhlanganisela ibeka isiteji sezinhlelo zokusebenza zobuchwepheshe ezizimele, ezisebenza kahle, neziklanyelwe, ezithembisa intuthuko yesikhathi esizayo ejabulisayo yezimboni kanye nokusetshenziswa kwansuku zonke kwezobuchwepheshe.

Amathuluzi nezinhlaka zokuqinisa ukufunda

Njengoba sihlole izinhlelo zokusebenza ezihlukahlukene nokuhlanganiswa kobuchwepheshe bokufunda okuqiniswayo, isidingo samathuluzi athuthukile okuthuthukisa, ukuhlola, kanye nokucwengisiswa kwalezi zinhlelo siyaba sobala. Lesi sigaba sigqamisa izinhlaka ezibalulekile kanye namathuluzi abalulekile ekwakheni izixazululo ezisebenzayo ze-RL. Lawa mathuluzi enzelwe ukuhlangabezana nezidingo zendawo eguquguqukayo nezinselele eziyinkimbinkimbi i-RL ebhekene nazo, ukuthuthukisa kokubili ukusebenza kahle nomthelela wezinhlelo zokusebenza ze-RL. Ake sibhekisise amanye amathuluzi abalulekile athuthukisa inkambu ye-RL:

• Ama-TensorFlow Agents (ama-TF-Agents). Ikhithi yamathuluzi enamandla ngaphakathi kwe-ecosystem ye-TensorFlow, i-TF-Agents isekela uhlu olubanzi lwama-algorithms futhi ifaneleka ngokukhethekile ukuhlanganisa amamodeli athuthukile nokufunda okujulile, ephelelisa intuthuko okukhulunywe ngayo ekuqaleni ekuhlanganiseni okujulile kokufunda.
• Ijimi ye-OpenAI. Idume ngezimo zayo ezihlukene zokulingisa—kusuka kumidlalo ye-Atari yakudala kuya ekulingiseni okuyinkimbinkimbi ngokomzimba—I-OpenAI Gym iyinkundla yokulinganisa evumela onjiniyela bahlole ama-algorithms e-RL kuzilungiselelo ezihlukahlukene. Kubalulekile ukuhlola ukuguquguquka kwe-RL ekusetheni ngokufana nalezo ezisetshenziswa ekuphathweni kwethrafikhi namagridi ahlakaniphile.
• RLlib. Isebenza kuhlaka lwe-Ray, i-RLlib ithuthukiselwe i-RL enwebekayo nesabalaliswayo, iphatha izimo eziyinkimbinkimbi ezifaka ama-ejenti amaningi, njengasekwenziweni kanye nokuxhumana kwezimoto ezizimele.
• I-PyTorch reinforcement learning (PyTorch-RL). Isebenzisa izici zekhompuyutha ezinamandla ze-PyTorch, le sethi yama-algorithms e-RL inikeza ukuguquguquka okudingekayo kumasistimu ajwayela ulwazi olusha, okubalulekile kumaphrojekthi adinga ukubuyekezwa njalo ngokusekelwe empendulweni.
• Izisekelo ezizinzile. Inguqulo ethuthukisiwe ye-OpenAI Baselines, Isisekelo Esizinzile sinikeza ama-algorithms e-RL abhalwe kahle futhi asebenziseka kalula asiza onjiniyela bacwengisise futhi basungule izindlela ezikhona ze-RL, ezibalulekile emikhakheni efana nokunakekelwa kwezempilo kanye nezezimali.

Lawa mathuluzi awagcini nje ngokwenza kahle ukuthuthukiswa kwezinhlelo zokusebenza ze-RL kodwa futhi adlala indima ebalulekile ekuhloleni, ekucwengeni nasekukhipheni amamodeli ezindaweni ezihlukahlukene. Behlome ngokuqonda okucacile kwemisebenzi yabo nokusetshenziswa kwabo, abathuthukisi nabacwaningi bangasebenzisa lawa mathuluzi ukuze bakhulise amathuba okufunda okuqinisiwe.

Ukusebenzisa ukulingisa okusebenzisanayo ukuqeqesha amamodeli e-RL

Ngemva kokunikeza imininingwane yamathuluzi abalulekile nezinhlaka ezisekela ukuthuthukiswa nokucwengwa kwamamodeli okufunda okuqiniswa, kubalulekile ukugxila lapho lawa mamodeli ahlolwa futhi acwengisiswa khona. Izimo zokufunda ezisebenzisanayo nezilingisayo zibalulekile ekuthuthukiseni izinhlelo zokusebenza ze-RL, ukuhlinzeka ngezilungiselelo eziphephile nezilawulwayo ezinciphisa ubungozi bomhlaba wangempela.

Izinkundla zokulingisa: Izinkundla zokuqeqesha ezingokoqobo

Amapulatifomu afana ne-Unity ML-Agents kanye ne-Microsoft AirSim ayisebenzi nje njengamathuluzi, kodwa njengamasango emihlaba engokoqobo, esebenzisanayo lapho ama-algorithms e-RL eqeqeshwa ngokuqinile. Lezi zinkundla zibalulekile ezizindeni ezifana nokushayela ngokuzenzakalelayo namarobhothi asemoyeni, lapho ukuhlola komhlaba wangempela kubiza futhi kuyingozi. Ngokulingisa okuningiliziwe, onjiniyela bangaphonsela inselelo futhi balungise amamodeli e-RL ngaphansi kwezimo ezihlukahlukene neziyinkimbinkimbi, ezifana ngokuseduze nokungabikezeli komhlaba wangempela.

Ukusebenzisana okunamandla ekufundeni

Imvelo eguquguqukayo yezindawo zokufunda ezisebenzisanayo ivumela amamodeli e-RL ukuthi azijwayeze imisebenzi futhi azivumelanise nezinselele ezintsha ngesikhathi sangempela. Lokhu kuzivumelanisa nezimo kubalulekile kumasistimu e-RL ahloselwe izinhlelo zokusebenza zomhlaba wangempela ezinamandla, njengokuphatha iphothifoliyo yezezimali noma ukuthuthukisa amasistimu wethrafikhi yasemadolobheni.

Iqhaza ekuthuthukisweni okuqhubekayo nasekuqinisekiseni

Ngaphandle kokuqeqeshwa kokuqala, lezi zindawo zibalulekile ekuthuthukisweni okuqhubekayo nokuqinisekiswa kwamamodeli okufunda okuqiniswa. Bahlinzeka ngenkundla yonjiniyela ukuze bahlole amasu amasha nezimo, bahlole ukuqina nokuvumelana nezimo kwama-algorithms. Lokhu kubalulekile ekwakheni amamodeli anamandla akwazi ukuphatha izinto eziyinkimbinkimbi zomhlaba wangempela.

Ukwandisa ucwaningo nomthelela wezimboni

Kubacwaningi, lezi zindawo zifinyeza i-loop yempendulo ekuthuthukisweni kwemodeli, kube lula ukuphindaphinda okusheshayo nokuthuthukiswa. Kuzinhlelo zokusebenza zezentengiselwano, baqinisekisa ukuthi amasistimu e-RL ahlolwa ngokucophelela futhi athuthukiswe ngaphambi kokuthunyelwa ezindaweni ezibalulekile ezifana nokunakekelwa kwezempilo nezezimali, lapho ukunemba nokwethembeka kubalulekile.

Ngokusebenzisa izindawo zokufunda ezisebenzisanayo nezilingisayo kunqubo yokuthuthukiswa kwe-RL, ukusetshenziswa okungokoqobo nokusebenza kahle kwalezi zindlela eziyinkimbinkimbi zokusebenzisa ingqondo kuyathuthukiswa. Lezi zinkundla ziguqula ulwazi lwethiyori lube ukusetshenziswa komhlaba wangempela futhi zithuthukise ukunemba nokusebenza kahle kwezinhlelo ze-RL, zilungiselela indlela yokudalwa kobuchwepheshe obuhlakaniphile, obuguquguqukayo.

Izinzuzo nezinselele zokufunda okuqiniswayo

Ngemva kokuhlola amathuluzi anhlobonhlobo, ukubona indlela asetshenziswa ngayo ezindaweni ezihlukene njengezimoto zokunakekelwa kwempilo nezimoto ezizishayelayo, nokufunda mayelana nemibono eyinkimbinkimbi efana nelophu yempendulo yokufunda eqinisayo nendlela esebenza ngayo ngokufunda okujulile, manje sesizokwenza bheka izinzuzo ezinkulu nezinselele zokufunda okuqiniswayo. Le ngxenye yengxoxo yethu izogxila ekutheni i-RL ixazulula kanjani izinkinga ezinzima futhi ibhekana nezinkinga zomhlaba wangempela, isebenzisa esikufundile ekuhloleni kwethu okuningiliziwe.

Izinzuzo

• Ukuxazulula izinkinga eziyinkimbinkimbi. I-Reinforcement learning (RL) ihamba phambili ezindaweni ezingalindelekile neziyinkimbinkimbi, ngokuvamile ezenza kangcono kunochwepheshe abangabantu. Isibonelo esihle i-AlphaGo, uhlelo lwe-RL oluwine umdlalo walo nompetha bomhlaba kugeyimu ye-Go. Ngale kwemidlalo, i-RL isebenze ngokumangazayo nakwezinye izindawo. Isibonelo, ekuphathweni kwamandla, amasistimu e-RL athuthukise ukusebenza kahle kwamagridi kagesi ngaphezu kwalokho ochwepheshe ababecabanga ukuthi kungenzeka. Le miphumela ibonisa ukuthi i-RL ingathola kanjani izixazululo ezintsha iyodwa, inikeze amathuba ajabulisayo ezimbonini ezihlukahlukene.
• Ukuvumelana nezimo okuphezulu. Ikhono le-RL lokujwayela ngokushesha izimo ezintsha liwusizo kakhulu ezindaweni ezifana nezimoto ezizishayelayo kanye nokuhweba ngamasheya. Kule mikhakha, amasistimu e-RL angashintsha amasu awo ngokushesha ukuze afane nezimo ezintsha, abonise ukuthi avumelana nezimo kangakanani. Isibonelo, ukusebenzisa i-RL ukuze uguqule amasu okuhweba lapho amashifu emakethe afakazele ukuthi asebenza kakhulu kunezindlela ezindala, ikakhulukazi ngezikhathi zemakethe ezingalindelekile.
• Ukwenza izinqumo ezizimele. Izinhlelo zokufunda eziqinisayo zisebenza ngokuzimela ngokufunda ekusebenzelaneni okuqondile nendawo ezikuyo. Lokhu kuzimela kubalulekile ezindaweni ezidinga ukuthathwa kwezinqumo okusheshayo, okuqhutshwa idatha, njengokuzulazula kwerobhothi nokunakekelwa kwezempilo komuntu siqu, lapho i-RL ithunga izinqumo ngokusekelwe kudatha yesiguli eqhubekayo.
• Ukungafinyeleli. Ama-algorithms e-RL akhelwe ukuphatha ubunzima obukhulayo futhi asebenze kahle ezinhlelweni eziningi ezahlukahlukene. Leli khono lokukala lisiza amabhizinisi ukuthi akhule futhi azivumelanise nezimo ezindaweni ezifana nokuthenga ku-inthanethi kanye nekhompyutha yamafu, lapho izinto zihlala zishintsha.
• Ukufunda okuqhubekayo. Ngokungafani namanye amamodeli e-AI angase adinge ukuqeqeshwa kabusha ngezikhathi ezithile, amasistimu e-RL ahlala efunda futhi ethuthuka ekusebenzisaneni okusha, okuwenza asebenze kahle kakhulu emikhakheni efana nokugcinwa kokuqagela, lapho eshintsha khona amashejuli ngokusekelwe kudatha yesikhathi sangempela.

Izinselele

• Ukuqina kwedatha. I-RL idinga idatha eningi nokusebenzisana okuvamile, okunzima ukukuthola ekuhlolweni kwangaphambi kwesikhathi kwezimoto ezizishayelayo. Nakuba ukuthuthukiswa kokulingiswa kanye nokwenza idatha yokwenziwa kusinikeza amasethi edatha okuqeqesha angcono, ukuthola idatha yomhlaba wangempela yekhwalithi ephezulu kuseyinselelo enkulu.
• Ubunzima bomhlaba wangempela. Impendulo engalindelekile nehamba kancane kuzilungiselelo zangempela yenza amamodeli e-RL aqeqeshe kube nzima. Ama-algorithms amasha athuthukisa indlela lawa mamodeli akusingatha ngayo ukubambezeleka, kodwa ukuzivumelanisa nokungabikezeli kwezimo zomhlaba wangempela kusaletha inselele enzima.
• Ubunkimbinkimbi bomklamo womvuzo. Kuyinselele ukudala amasistimu okuklomelisa abhalansisa izenzo ezisheshayo nezinjongo zesikhathi eside. Imizamo efana nokwenza amasu okufunda okuqinisa okuphambene ibalulekile, kodwa awakabuxazululi ngokuphelele ubunkimbinkimbi kuzinhlelo zokusebenza zomhlaba wangempela.
• Izimfuno eziphezulu zekhompyutha. Ama-algorithms e-RL adinga amandla amaningi ekhompuyutha, ikakhulukazi uma esetshenziswa ezimeni ezinkulu noma eziyinkimbinkimbi. Ngisho noma kunemizamo yokwenza lawa ma-algorithms asebenze kahle kakhudlwana nokusebenzisa ihadiwe yekhompuyutha enamandla njenge-Graphics Processing Units (GPUs) kanye ne-Tensor Processing Units (TPUs), izindleko kanye nenani lezinsiza ezidingekayo kusengaba phezulu kakhulu ezinhlanganweni eziningi.
• Ukusebenza kwesampula. Ukufunda ukuqinisa ngokuvamile kudinga idatha eningi ukuze kusebenze kahle, okuyinkinga enkulu ezindaweni ezifana nerobhothi noma ukunakekelwa kwezempilo lapho ukuqoqa idatha kungase kubize noma kube yingozi. Kodwa-ke, amasu amasha okufunda ngaphandle kwenqubomgomo kanye nokufunda kokuqinisa iqoqo enza kube nokwenzeka ukufunda okwengeziwe kudatha encane. Naphezu kwalokhu kuthuthukiswa, kuseyinselele ukuthola imiphumela emihle kakhulu ngamaphoyinti edatha ambalwa.

Izikhombisi-ndlela zesikhathi esizayo nezinye izinselele

Njengoba sibheke esikhathini esizayo, ukufunda okuqiniswayo sekumi ngomumo ukubhekana nezinselele ezikhona kanye nokwandisa ukusetshenziswa kwakho. Nansi intuthuko ethile nokuthi kulindeleke ukuthi ibhekane kanjani nalezi zinselele:

• Izinkinga zokwehla. Nakuba i-RL ingakala ngokwemvelo, isadinga ukuphatha izindawo ezinkulu neziyinkimbinkimbi ngokwengeziwe. Ukusungulwa kwezinhlelo zama-ejenti amaningi kulindeleke ukuthi kuthuthukise ukusatshalaliswa kwemisebenzi yokubala, okunganciphisa kakhulu izindleko futhi kuthuthukise ukusebenza ngezikhathi eziphakeme, njengasesikhathini sangempela sokuphathwa kwethrafikhi yedolobha lonke noma izikhathi zokulayisha okuphezulu kukhompyutha yamafu.
• Ukuxaka kwezinhlelo zokusebenza zomhlaba wangempela. Ukuvala igebe phakathi kwezindawo ezilawulwayo kanye nokungabikezeli kwempilo yangempela kusalokhu kuseqhulwini. Ucwaningo lugxile ekuthuthukiseni ama-algorithms anamandla akwazi ukusebenza ngaphansi kwezimo ezihlukahlukene. Isibonelo, amasu okufunda okuguquguqukayo, ahlolwe kumaphrojekthi okuhlola okuzulazula okuzenzakalelayo ezimeni zesimo sezulu esishintshashintshayo, alungiselela i-RL ukuze isingathe ubunzima obufanayo bomhlaba wangempela ngempumelelo kakhudlwana.
• Idizayini yesistimu yomvuzo. Ukuklama amasistimu okuklomelisa aqondanisa izenzo zesikhathi esifushane nezinjongo zesikhathi eside kuyaqhubeka nokuba inselele. Imizamo yokucacisa nokwenza lula ama-algorithms izosiza ukudala amamodeli okulula ukuwahumusha nokuqondanisa nezinjongo zenhlangano, ikakhulukazi kwezezimali nokunakekelwa kwezempilo, lapho imiphumela enembayo ibalulekile.
• Ukuhlanganiswa nentuthuko yesikhathi esizayo. Ukuhlanganiswa kwe-RL nobuchwepheshe be-AI obuthuthukisiwe obufana namanethiwekhi adversarial akhiqizayo (ama-GAN) nokucutshungulwa kolimi lwemvelo (NLP) kulindeleke ukuthi kuthuthukise kakhulu amakhono e-RL. Le synergy ihlose ukusebenzisa amandla obuchwepheshe obunye ukukhulisa ukuguquguquka nokusebenza kwe-RL, ikakhulukazi ezimeni eziyinkimbinkimbi. Lezi ntuthuko zihlelelwe ukwethula izinhlelo zokusebenza ezinamandla nezisebenza emhlabeni wonke emikhakheni eyahlukene.

Ngokuhlaziya kwethu okuningiliziwe, kuyacaca ukuthi nakuba i-RL inikeza amandla amakhulu okuguqula imikhakha eyahlukene, impumelelo yayo incike ekunqobeni izinselele ezinkulu. Ngokuqonda ngokugcwele amandla kanye nobuthakathaka be-RL, abathuthukisi, nabacwaningi bangasebenzisa ngempumelelo lobu buchwepheshe ukuze baqhube ukuqanjwa kabusha nokuxazulula izinkinga eziyinkimbinkimbi emhlabeni wangempela.

Izimiso zokuziphatha ekuqiniseni ukufunda

Njengoba siphetha ukuhlola kwethu okubanzi kokufunda okuqinisiwe, kubalulekile ukubhekana nemithelela yako yezimiso zokuziphatha—isici sokugcina kodwa esibalulekile sokuphakela amasistimu e-RL kuzimo zomhlaba wangempela. Ake sixoxe ngezibopho ezibalulekile nezinselele eziphakamayo ngokuhlanganiswa kwe-RL nobuchwepheshe bansuku zonke, sigqamisa isidingo sokucatshangelwa ngokucophelela kokusetshenziswa kwayo:

• Ukuzenzela izinqumo. Ukufunda ukuqinisa kwenza amasistimu enze izinqumo ezizimele, ezingathinta kakhulu ukuphepha nokuphila kwabantu. Isibonelo, ezimotweni ezizimele, izinqumo ezenziwa ama-algorithms e-RL zithinta ngokuqondile ukuphepha kwabo bobabili abagibeli nabahamba ngezinyawo. Kubalulekile ukuqinisekisa ukuthi lezi zinqumo azilimazi abantu ngabanye nokuthi kunezinqubo eziqinile ezikhona zokuhluleka kwesistimu.
• Izinkinga zobumfihlo. Amasistimu e-RL ngokuvamile acubungula inani elikhulu ledatha, kuhlanganise nolwazi lomuntu siqu. Ukuvikelwa kobumfihlo okuqinile kufanele kusetshenziswe ukuze kuqinisekiswe ukuthi ukuphathwa kwedatha kulandela izindinganiso ezingokomthetho nezokuziphatha, ikakhulukazi uma amasistimu esebenza ezindaweni zomuntu siqu njengasekhaya noma kumadivayisi omuntu siqu.
• Ukuchema nokungenzeleli. Ukugwema ukuchema kuyinselelo enkulu ekusetshenzisweni kwe-RL. Njengoba lezi zinhlelo zifunda ezindaweni zazo, ukuchema kudatha kungaholela ezinqumweni ezingalungile. Le nkinga ibaluleke kakhulu ezinhlelweni zokusebenza ezifana namaphoyisa aqagelayo noma ukuqasha, lapho ama-algorithms achemile angase aqinise ukungabi nabulungisa okukhona. Onjiniyela kufanele basebenzise izindlela zokususa ukuchema futhi bahlole ngokuqhubekayo ukulunga kwamasistimu abo.
• Ukuziphendulela nokubonakala obala. Ukuze kuncishiswe lezi zingozi, kufanele kube nemihlahlandlela ecacile nemithethonqubo yezinqubo zokufunda zokuqinisa ukuziphatha. Onjiniyela nezinhlangano kufanele zibe sobala mayelana nendlela amasistimu abo e-RL azenza ngayo izinqumo, idatha abayisebenzisayo, nezinyathelo ezithathwayo ukuze kubhekwane nokukhathazeka kokuziphatha. Ngaphezu kwalokho, kufanele kube nezindlela zokuziphendulela kanye nezinketho zokuthola usizo uma uhlelo lwe-RL ludala umonakalo.
• Ukuthuthukiswa kokuziphatha nokuqeqeshwa: Phakathi nezigaba zokuthuthukiswa nokuqeqeshwa, kubalulekile ukucabangela ukutholwa kokuziphatha kwedatha nokubandakanya imibono eyahlukahlukene. Le ndlela isiza ukubhekana kusengaphambili nokuchema okungaba khona futhi iqinisekise ukuthi amasistimu e-RL aqinile futhi alungile kuzo zonke izimo ezihlukahlukene zokusetshenziswa.
• Umthelela emsebenzini. Njengoba izinhlelo ze-RL zisetshenziswa kakhulu ezimbonini ezahlukene, kubalulekile ukuthi kubhekwe ukuthi ziyithinta kanjani imisebenzi. Abantu abaphethe kudingeka bacabange futhi banciphise noma yimiphi imiphumela engemihle emisebenzini, njengabantu abalahlekelwa imisebenzi noma imisebenzi eshintshayo. Kufanele baqinisekise ukuthi njengoba imisebenzi eminingi iba ngomshini, kunezinhlelo zokufundisa amakhono amasha nokudala amathuba emisebenzi emikhakheni emisha.

Ngokuhlaziya kwethu okuningiliziwe, kuyacaca ukuthi nakuba i-RL inikeza amandla amangalisayo okuguqula imikhakha eyahlukene, ukucatshangelwa ngokucophelela kwalezi zindlela zokuziphatha kubalulekile. Ngokubona nokubhekana nalokhu kucatshangelwa, abathuthukisi nabacwaningi bangaqinisekisa ukuthi ubuchwepheshe be-RL buthuthuka ngendlela ehambisana nemikhuba namagugu omphakathi.

Isiphetho

Ukungena kwethu ngokujulile ekufundeni kokuqinisa (RL) kusibonise amandla ako anamandla okuguqula imikhakha eminingi ngemishini yokufundisa ukufunda nokwenza izinqumo ngenqubo yokuhlola namaphutha. Ukuzivumelanisa nezimo kwe-RL nekhono lokuqhubeka nokwenza ngcono kuyenza ibe inketho evelele yokuthuthukisa yonke into kusukela ezimotweni ezizishayelayo kuya ezinhlelweni zokunakekelwa kwempilo. Kodwa-ke, njengoba i-RL iba ingxenye enkulu yempilo yethu yansuku zonke, kufanele sicabangele ngokujulile imithelela yayo yokuziphatha. Kubalulekile ukugxila ekungenzeleli, ubumfihlo, nokuvuleleka njengoba sihlola izinzuzo nezinselelo zalobu buchwepheshe. Futhi, njengoba i-RL ishintsha imakethe yemisebenzi, kubalulekile ukusekela izinguquko ezisiza abantu ukuthuthukisa amakhono amasha nokudala imisebenzi emisha. Uma sibheka phambili, akufanele nje sihlose ukuthuthukisa ubuchwepheshe be-RL kodwa futhi siqinisekise ukuthi sihlangabezana nezindinganiso eziphakeme zokuziphatha ezizuzisa umphakathi. Ngokuhlanganisa ukuqamba okusha nomthwalo wemfanelo, asikwazi ukusebenzisa i-RL hhayi nje ukwenza intuthuko yezobuchwepheshe kodwa futhi sikhuthaze izinguquko ezinhle emphakathini. Lokhu kuphetha ukubuyekeza kwethu okujulile, kodwa kuseyisiqalo nje sokusebenzisa i-RL ngokuzibophezela ukwakha ikusasa elihlakaniphile nelingenzeleli.