Ndapota tsanangura makirasi makuru eReinforcement Learning (RL) mukati meMachine Learning uye matambudziko api avanoedza kugadzirisa.
Context:Kudzidza kunosimbisa kushamwaridzana Basa rekudzidza rinosimbisa rinobatanidza zvinhu zvemabasa ekudzidza otomatiki uye mabasa ekuronga maitiro ekudzidza anotarisirwa. Mumabasa okudzidza nokusimbisa, gadziriro yokudzidza inotaurirana nemhoteredzo yayo iri mumutsetse wakavharwa.  Kudzidza kwakadzama kwekusimbisa Nzira iyi inowedzera kudzidzira kusimbisa nekushandisa yakadzika neural network uye pasina kunyatsogadzira nzvimbo yenyika. Basa rekudzidza mitambo yeATARI neGoogle DeepMind rakawedzera kutarisisa kudzidzira kwakadzama kana kudzidzira kwekupedzisira.  Kudzidza kwakadzama kunosimbisa kunopesana Kudzidza kwakadzama kwekusimbisa kwakashata inzvimbo inoshanda yekutsvagisa mukudzidza kwekusimbisa inotarisa pane kusagadzikana kwemitemo yakadzidziswa. Munharaunda ino yokutsvakurudza zvimwe zvidzidzo pakutanga zvakaratidza kuti mitemo yokudzidza yokusimbisa inogona kupesvedzera kusanzwisisika. Kunyange zvazvo dzimwe nzira dzakarongwa kuti dzigadzirise zvinhu izvi, muongororo dzichangobva kuitwa zvakaratidzwa kuti mhinduro idzi dzakarongwa hadzisi dzakakwana pakuratidza zvinetso zvemazuva ano zvemitemo yokudzidza kwakadzama kunosimbisa.  Kudzidza kunosimbisa kusinganzwisisiki Nokutanga fuzzy inference muRL, approximating mamiriro-chiito ukoshi basa pamwe fuzzy mitemo mune chinopfuurira nzvimbo anova zvinobvira. IF-Ipapo chimiro mitemo fuzzy kuti nzira iyi yakakodzera kutaura migumisiro ari chimiro pedyo mutauro chaiwo. Kuwedzera FRL neFuzzy Rule Interpolation kunobvumira kushandiswa kwehukuru hwakaderedzwa hwakaderera husina kujeka-hwaro hwekutonga kusimbisa mitemo yemakadhi (yakanyanya kukosha nyika-chiito kukosha).  Kudzidza kunosimbisa Mukudzidza kunosimbisa (IRL), hapana basa remubairo rinopihwa. Panzvimbo pezvo, basa romubairo rinofungidzirwa kupiwa mufambiro unocherekedzwa unobva kunyanzvi. Pfungwa yacho ndeyokutevedzera maitiro anoonekwa, ayo anowanzova akanaka kana kuti ari pedyo neakanaka.  Kudzidza kunosimbisa kwakachengeteka Safe kusimbisa kudzidza (SRL) rinogona kurondedzerwa sezvo muitiro kudzidza policies kuti maximize tarisiro kudzoka matambudziko umo zvakakosha kuti vave nechokwadi zvine hurongwa kuita uye / kana kuremekedza kuchengeteka constraints panguva kudzidza uye / kana deployment pezvakaitwa.
Kusimbisa Kudzidza inzvimbo yeMuchina Kudzidza iyo inoshanda mune dambudziko nzvimbo kana nharaunda uko mumiririri kana Kusimbisa Kudzidza algorithm, inoshandisa nzwisiso yezvakaitika zvakapfuura bvunzo mhedzisiro uye nzira dzinogona kuitika kuburikidza nharaunda kuverenga mutemo unogadzirisa chinangwa che mubairo wakawedzerwa.  Tichifunga nezvezvinhu zvakasiyana-siyana zvinogona kuitwa neRL, pane nzira dzakasiyana-siyana dzingashandiswa nemurapi uye dzinogona kuiswa mumapoka matanhatu akasiyana: 1. Zvinhu zvose. Yakabatanidzwa RL - iyo inosanganisa nzira dzechinyakare dzeMuchina Kudzidza kupatsanura nekudzidza otomatiki pane zvisina kujairika, kana zvakapatsanurwa zvakapatsanurwa. 2. Kuziva Mwari. Deep RL - iyo inoshandisa tsika dzakadzika neural network asi inobvumidza kuchinjika uye kushomeka kwematanho akafanotsanangurwa uye nzvimbo yenyika. 3. Kuita zvinhu nenzira yakanaka. Adversarial Deep RL - apo magumo anofananidzwa achishandisa kusagadzikana mumamiriro akachengetwa muDeep Neural Networks uye anoedza kuwana kushaya simba mumamodeli aya. 4. Fuzzy RL - iyo inoshandisa tsanangudzo yepedyo yemutauro wechisikigo yemitemo isina kujeka kana-ipapo iyo inosarudza kuverenga kukosha kwemhedzisiro. 5. Kuita zvinhu zvakanaka. Inverse RL - iyo inobvisa iyo yakajairika mubairo basa rekuongorora chikamu chemuenzaniso uye pachinzvimbo inoisa munhu kuti atarise uye kuongorora mhedzisiro. 6. Kuita basa rokuparidza Safe RL - ndiyo nzira yokurondedzera mitemo kuti anotarisawo maitiro mumiririri ari zvakatipoteredza, zvokuti avo mumiririri matanho zvine musoro kana kuremekedza kuchengeteka constraints.