{"id":52119,"date":"2019-11-01T00:00:00","date_gmt":"2019-10-31T21:00:00","guid":{"rendered":"https:\/\/prohoster.info\/blog\/blog_prohoster\/kak-ustroen-gibridnyj-igrovoj-ii-i-v-chyom-ego-preimushhestva"},"modified":"2020-02-18T13:59:47","modified_gmt":"2020-02-18T10:59:47","slug":"kak-ustroen-gibridnyj-igrovoj-ii-i-v-chyom-ego-preimushhestva","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sq\/blog\/news\/kak-ustroen-gibridnyj-igrovoj-ii-i-v-chyom-ego-preimushhestva","title":{"rendered":"Si funksionon IA hibride n\u00eb loj\u00ebra dhe cilat jan\u00eb avantazhet e saj","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Nd\u00ebrsa vazhdojm\u00eb tem\u00ebn q\u00eb kemi shtruar dikur n\u00eb blogun ton\u00eb t\u00eb inteligjenc\u00ebs artificiale n\u00eb loj\u00ebra<\/a><\/noindex> do t\u00eb flasim p\u00ebr sa e aplikueshme \u00ebsht\u00eb m\u00ebsimi i makineris\u00eb p\u00ebr t\u00eb dhe n\u00eb \u00e7far\u00eb forme. P\u00ebrvoj\u00ebn e tij dhe zgjidhjet e zgjedhura mbi k\u00ebt\u00eb baz\u00eb ndau<\/a><\/noindex> eksperti i \u00e7\u00ebshtjeve t\u00eb IA n\u00eb Apex Game Tools, Jakob Rasmussen.<\/p>\n

\"Si
\n
\nN\u00eb vitet e fundit, ka pasur shum\u00eb diskutime se m\u00ebsimi i makineris\u00eb do t\u00eb ndryshoj\u00eb rr\u00ebnj\u00ebsisht industrin\u00eb e loj\u00ebrave, pasi kjo teknologji tashm\u00eb ka b\u00ebr\u00eb p\u00ebrparime t\u00eb m\u00ebdha n\u00eb shum\u00eb aplikacione t\u00eb tjera digjitale. Por nuk duhet t\u00eb harrojm\u00eb se loj\u00ebrat jan\u00eb shum\u00eb m\u00eb komplekse se nj\u00eb simulues i vozitjes, nj\u00eb program p\u00ebr menaxhimin e droneve ose algoritmet p\u00ebr njohjen e fytyrave n\u00eb imazhe. <\/a><\/noindex><\/p>\n

Nd\u00ebrkoh\u00eb q\u00eb industria e loj\u00ebrave vazhdon t\u00eb p\u00ebrdor\u00eb metoda tradicionale t\u00eb IA-s\u00eb, si metoda e automatave t\u00eb fundme, drur\u00ebt e sjelljes dhe \u2014 koh\u00ebt e fundit gjithnj\u00eb e m\u00eb shpesh \u2014 IA e bazuar n\u00eb utilitet (sistemet e bazuara n\u00eb dobi). K\u00ebto IA quhen gjithashtu IA t\u00eb bazuar n\u00eb dizajn ose sisteme ekspertiz\u00eb. Por po b\u00ebhet gjithnj\u00eb e m\u00eb e qart\u00eb \u2014 sidomos p\u00ebr lojtar\u00ebt \u2014 se k\u00ebto sisteme jan\u00eb gjithnj\u00eb e m\u00eb pak t\u00eb p\u00ebrshtatshme p\u00ebr krijimin e armik\u00ebve v\u00ebrtet t\u00eb avancuar, t\u00eb aft\u00eb p\u00ebr t\u00eb imituar sjelljen e lojtar\u00ebve. Kjo \u00ebsht\u00eb ve\u00e7an\u00ebrisht e v\u00ebrtet\u00eb p\u00ebr zgjidhjet krijuese. Kjo mund t\u00eb shpjegohet me faktin se zhvilluesit e inteligjenc\u00ebs artificiale nuk jan\u00eb n\u00eb gjendje t\u00eb marrin parasysh t\u00eb gjitha taktikat dhe strategjit\u00eb e mundshme t\u00eb sjelljes dhe t\u00eb realizojn\u00eb me sukses ato n\u00eb sistemet tradicionale t\u00eb IA-s\u00eb. P\u00ebr lojtar\u00ebt, kjo shpesh b\u00ebhet monotone dhe e parashikueshme t\u00eb luash me nj\u00eb armik, linja e sjelljes s\u00eb t\u00eb cilit \u00ebsht\u00eb leht\u00ebsisht e memorizueshme.<\/p>\n

Ky rezultat vjen p\u00ebr shum\u00eb arsye, por nj\u00eb nga arsyet kryesore \u00ebsht\u00eb pamund\u00ebsia e IA-s\u00eb p\u00ebr t\u00eb m\u00ebsuar. Prandaj, kur krijojm\u00eb inteligjenc\u00ebn artificiale t\u00eb armikut, automatikisht na vjen n\u00eb mendje zgjidhja e kalimit n\u00eb m\u00ebsimin e makineris\u00eb, i cili ka treguar rezultate t\u00eb shk\u00eblqyera n\u00eb shum\u00eb aplikacione t\u00eb tjera. Por ka disa nuanca q\u00eb duhet t\u00eb merren parasysh. Sidoqoft\u00eb, IA e loj\u00ebrave duhet t\u00eb jet\u00eb n\u00eb gjendje t\u00eb adaptohet n\u00eb \u00e7do situat\u00eb dhe t\u00eb shfryt\u00ebzoj\u00eb avantazhet q\u00eb ajo i ofron, si dhe t\u00eb p\u00ebrshtatet me stile t\u00eb ndryshme loje t\u00eb kund\u00ebrshtar\u00ebve \u2014 lojtar\u00eb t\u00eb gjall\u00eb dhe IA t\u00eb tjera. <\/p>\n

<\/p>\n

Si \u00ebsht\u00eb situata tani<\/h3>\n

\nKompania britanike DeepMind, e cila merret me zhvillimin e inteligjenc\u00ebs artificiale, koh\u00ebt e fundit tregoi se si AI mund t\u00eb m\u00ebsoj\u00eb vet\u00eb t\u00eb luaj\u00eb loj\u00ebra, t\u00eb shpjer\u00eb rregullat e tyre dhe t\u00eb gjej\u00eb m\u00ebnyra p\u00ebr t\u00eb kaluar loj\u00ebn ose p\u00ebr t\u00eb fituar \u2014 deri tani, vet\u00ebm si shembuj me loj\u00ebra t\u00eb thjeshta, si loj\u00ebrat e hershme. Atari<\/a><\/noindex> \u2014 si\u00e7 jan\u00eb, p\u00ebr shembull, shahu dhe loja japoneze logjike go. Rezultatet e fituara p\u00ebr to tregojn\u00eb se inteligjenca artificiale \u00ebsht\u00eb n\u00eb gjendje t\u00eb formuloj\u00eb nj\u00eb vler\u00ebsim t\u00eb p\u00ebrshtatsh\u00ebm p\u00ebr at\u00eb q\u00eb po ndodh n\u00eb fush\u00ebn e loj\u00ebs. N\u00ebse flasim p\u00ebr adaptimin e AI ndaj stileve t\u00eb ndryshme t\u00eb loj\u00ebs s\u00eb kund\u00ebrshtarit, rezultatet deri tani nuk jan\u00eb aq impresionuese.<\/p>\n

N\u00eb dit\u00ebt e sotme, rrjetet neurale kan\u00eb m\u00ebsuar tashm\u00eb t\u00eb njohin imazhe dhe t\u00eb drejtojn\u00eb automjetet. Por k\u00ebto funksione mund t\u00eb realizohen gjithashtu duke p\u00ebrdorur arkitektura relativisht t\u00eb thjeshta, edhe n\u00ebse p\u00ebrfundimisht ato rezultojn\u00eb t\u00eb jen\u00eb mjaft t\u00eb thella dhe t\u00eb m\u00ebdha. P\u00ebr shembull, AI p\u00ebr njohjen e imazheve n\u00eb Facebook ka thell\u00ebsi rreth 100 shtresash, duke e b\u00ebr\u00eb at\u00eb t\u00eb ngjash\u00ebm me trurin biologjik \u2014 p\u00ebr sa i p\u00ebrket numrit dhe kompleksitetit t\u00eb lidhjeve midis neuroneve q\u00eb formojn\u00eb nj\u00eb rrjet t\u00eb madh. <\/p>\n

<\/p>\n

AI n\u00eb loj\u00ebra<\/h3>\n

\nSa i p\u00ebrket aplikimit t\u00eb m\u00ebsimit t\u00eb makinerive n\u00eb industrin\u00eb e loj\u00ebrave, k\u00ebtu ekzistojn\u00eb disa kufizime, p\u00ebr shkak t\u00eb t\u00eb cilave nuk \u00ebsht\u00eb gjithmon\u00eb e mundur t\u00eb p\u00ebrdorin k\u00ebt\u00eb lloj arkitekture. K\u00ebto p\u00ebrfshijn\u00eb k\u00ebrkesat sistemore, ve\u00e7an\u00ebrisht ato q\u00eb lidhen me CPU-n\u00eb, t\u00eb cilat p\u00ebrcaktojn\u00eb aft\u00ebsin\u00eb e kompjuterit p\u00ebr t\u00eb p\u00ebrpunuar struktur\u00ebn e nd\u00ebrlikuar t\u00eb loj\u00ebs dhe p\u00ebrshtatshm\u00ebrin\u00eb e tij p\u00ebr tregimin e loj\u00ebrave dhe loj\u00ebn. <\/p>\n

K\u00ebshtu del q\u00eb n\u00eb shum\u00eb loj\u00ebra p\u00ebr t\u00eb realizuar nj\u00eb sistem t\u00eb avancuar t\u00eb inteligjenc\u00ebs artificiale, nuk ka mund\u00ebsi t\u00eb organizohet ose pajisja e nevojshme harduerike dhe aq m\u00eb pak nj\u00eb grup server\u00ebsh, si\u00e7 ekziston, p\u00ebr shembull, p\u00ebr rrjetet e njohjes s\u00eb imazheve n\u00eb Facebook. Ndonj\u00ebher\u00eb, disa IA duhet t\u00eb punojn\u00eb n\u00eb t\u00eb nj\u00ebjt\u00ebn koh\u00eb \u2014 dhe jo vet\u00ebm n\u00eb kompjuter\u00eb, por edhe n\u00eb pajisje mobile dhe n\u00eb platforma m\u00eb pak t\u00eb fuqishme. T\u00eb gjitha k\u00ebto vendosin kufizime mbi p\u00ebrmasat dhe kompleksitetin e arkitektur\u00ebs s\u00eb m\u00ebsimit t\u00eb makinerive, pasi t\u00eb gjitha llogaritjet do t\u00eb kryhen gjithashtu me nj\u00eb koh\u00eb t\u00eb gjat\u00eb kornizash prej rreth 1 ose 2 milisekondash. Natyrisht, mund t\u00eb p\u00ebrdoren teknologji t\u00eb ndryshme optimizimi dhe shp\u00ebrndarje e ngarkes\u00ebs midis kornizave, por megjithat\u00eb nuk arrijm\u00eb t\u00eb heqim plot\u00ebsisht k\u00ebto kufizime.<\/p>\n

Problemet serioze p\u00ebr IA mund t\u00eb shkaktohen nga kompleksiteti i loj\u00ebs. Sepse n\u00eb loj\u00ebra t\u00eb tilla si, p\u00ebr shembull, StarCraft II, mekanika e loj\u00ebs \u00ebsht\u00eb shum\u00eb m\u00eb e komplikuar se n\u00eb loj\u00ebrat Atari. Prandaj, nuk duhet pritur q\u00eb me nj\u00eb frekuenc\u00eb t\u00eb dh\u00ebnash t\u00eb caktuar dhe me k\u00ebrkesat e njohura sistemike, m\u00ebsimi i makin\u00ebs t\u00eb ket\u00eb mund\u00ebsi t\u00eb studioj\u00eb t\u00eb gjith\u00eb shtetin e loj\u00ebs si nj\u00eb t\u00ebr\u00ebsi dhe t\u00eb nd\u00ebrveproj\u00eb me t\u00eb. Ashtu si nj\u00eb lojtar shpesh drejtohet nga intuita n\u00eb fazat e hershme t\u00eb loj\u00ebs, ashtu dhe IA duhet t\u00eb m\u00ebsoj\u00eb p\u00ebrpunimin fillestar t\u00eb gjendjes s\u00eb loj\u00ebs p\u00ebr ta thjesht\u00ebsuar kalimin e saj t\u00eb m\u00ebtejsh\u00ebm. P\u00ebr shembull, n\u00eb nj\u00eb nga t\u00eb fundit API p\u00ebr Starcraft II<\/a><\/noindex> n\u00eb harta shfaqet vet\u00ebm ajo informacion q\u00eb zhvilluesit e konsideruan t\u00eb r\u00ebnd\u00ebsish\u00ebm: n\u00eb nj\u00eb rast, IA p\u00ebrdori nj\u00eb pamje t\u00eb reduktuar t\u00eb gjith\u00eb territorit t\u00eb hart\u00ebs, n\u00eb rastin tjet\u00ebr \u2014 si nj\u00eb lojtar, ai mund t\u00eb l\u00ebvizte kamer\u00ebn, dhe k\u00ebshtu perceptimi i tij kufizohej n\u00eb informacionin n\u00eb ekran.<\/p>\n

\"Si
\nVizualizimi i loj\u00ebs IA AlphaStar kund\u00ebr lojtarit n\u00eb StarCraft II: n\u00eb screenshot jan\u00eb t\u00eb paraqitura \"v\u00ebzhgimet\" e pap\u00ebrpunuara fillestare, aktiviteti i rrjetit \u0627\u0644\u0639\u0635\u0628\u064a, disa nga veprimet e mundshme t\u00eb tij dhe koordinatat, si dhe rezultati i parashikuar i ndeshjes.<\/i><\/p>\n

Ky\u00e7\u00eb i r\u00ebnd\u00ebsish\u00ebm ky \u00ebsht\u00eb n\u00eb rastin e loj\u00ebrave. Shpesh her\u00eb, metodat e zakonshme t\u00eb zgjidhjes s\u00eb problemeve t\u00eb m\u00ebsimit t\u00eb makinerive nuk jan\u00eb t\u00eb aplikueshme p\u00ebr inteligjenc\u00ebn artificiale t\u00eb loj\u00ebrave. P\u00ebr shembull, zakonisht nuk \u00ebsht\u00eb e detyruar t\u00eb fitoj\u00eb ose t\u00eb b\u00ebj\u00eb gjith\u00e7ka q\u00eb \u00ebsht\u00eb e mundur p\u00ebr t\u00eb fituar, si\u00e7 ndodhi me loj\u00ebrat Atari. M\u00eb shpesh, roli i AI-s\u00eb \u00ebsht\u00eb q\u00eb ta b\u00ebj\u00eb kalimin e loj\u00ebs m\u00eb emocionues. Ajo mund t\u00eb duhet t\u00eb luaj\u00eb nj\u00eb rol dhe t\u00eb sillet ashtu si\u00e7 e parashikon karakteri i personazhit p\u00ebr t\u00eb cilin \u00ebsht\u00eb p\u00ebrgjegj\u00ebs. K\u00ebshtu, AI-t\u00eb e loj\u00ebrave jan\u00eb m\u00eb t\u00eb lidhura me dizajnin e loj\u00ebs dhe tregimin dhe duhet t\u00eb ken\u00eb mjetet e nevojshme p\u00ebr t\u00eb kontrolluar sjelljen e tyre p\u00ebr t\u00eb arritur q\u00ebllimet e caktuara. M\u00ebsimi i makinerive n\u00eb form\u00ebn e tij t\u00eb past\u00ebr nuk \u00ebsht\u00eb gjithmon\u00eb i p\u00ebrshtatsh\u00ebm p\u00ebr k\u00ebt\u00eb \u2014 k\u00ebshtu q\u00eb duhet t\u00eb k\u00ebrkohet di\u00e7ka tjet\u00ebr. <\/p>\n

<\/p>\n

Problemet praktike t\u00eb m\u00ebsimit t\u00eb makinerive<\/h3>\n

\nK\u00ebto probleme u shfaq\u00ebn gjat\u00eb zhvillimit t\u00eb inteligjenc\u00ebs artificiale t\u00eb bazuar n\u00eb m\u00ebsimin e makinerive p\u00ebr Unleash<\/a><\/noindex>, ku AI duhet t\u00eb sillet si lojtar\u00eb normal\u00eb \u2014 dometh\u00ebn\u00eb, t\u00eb jet\u00eb po aq fleksib\u00ebl dhe shpik\u00ebs. <\/p>\n

Si Starcraft II, Unleashed \u00ebsht\u00eb shum\u00eb m\u00eb komplekse se shah dhe go p\u00ebr Atari. Procesi i loj\u00ebs \u00ebsht\u00eb intuitiv dhe leht\u00ebsisht i kuptuesh\u00ebm, por p\u00ebr t\u00eb arritur me t\u00eb v\u00ebrtet\u00eb sukses, nevojiten disa aft\u00ebsi p\u00ebr t\u00eb menaxhuar met\u00ebn. Lojtari duhet t\u00eb krijoj\u00eb labirinthe, t\u00eb nxis\u00eb monstruozitetin ndaj armiqve dhe t\u00eb planifikoj\u00eb strategjin\u00eb e tij n\u00eb ekonomi, sulm dhe mbrojtje gjat\u00eb gjith\u00eb loj\u00ebs. P\u00ebr k\u00ebt\u00eb, ai duhet t\u00eb g\u00ebnjej\u00eb dhe t\u00eb parashikoj\u00eb l\u00ebvizjet e tjer\u00ebve, si dhe t\u00eb menaxhoj\u00eb met\u00ebn psikologjike \u2014 kjo e b\u00ebn pokerin di\u00e7ka m\u00eb shum\u00eb se nj\u00eb loj\u00eb statistike.<\/p>\n

\"Si
\nScreenshot nga Unleashed<\/i><\/p>\n

N\u00eb k\u00ebrkim t\u00eb arkitektur\u00ebs m\u00eb t\u00eb p\u00ebrshtatshme p\u00ebr k\u00ebto q\u00ebllime, teknologjit\u00eb si neuroevolucioni<\/a><\/noindex> dhe m\u00ebsimi i thell\u00eb u inkorporuan fillimisht n\u00eb loj\u00eb n\u00eb nj\u00eb form\u00eb praktikisht t\u00eb pandryshuar dhe u testuan se si do t\u00eb performonin ndryshe si AI kund\u00ebrshtar. <\/p>\n

Ishte katastrofike. <\/p>\n

Shpejt u b\u00eb e qart\u00eb se n\u00eb Unleashed duhej t\u00eb zgjidhnim shum\u00eb probleme globale, p\u00ebr t\u00eb cilat ishte e v\u00ebshtir\u00eb t\u00eb p\u00ebrshtatej m\u00ebsimi i makinerive. <\/p>\n

Nj\u00eb nga to \u00ebsht\u00eb nd\u00ebrtimi i nj\u00eb labirinti efektiv. Ashtu si n\u00eb shum\u00eb loj\u00ebra, ku q\u00ebllimi \u00ebsht\u00eb mbrojtja e kull\u00ebs, k\u00ebtu lojtar\u00ebt duhet t\u00eb nd\u00ebrtojn\u00eb nj\u00eb labirint p\u00ebrreth saj, p\u00ebrmes t\u00eb cilit do t\u00eb dep\u00ebrtojn\u00eb monstruoz\u00ebt. Atyre, nga ana tjet\u00ebr, duhet t'u b\u00ebhet ball\u00eb me arm\u00ebt, t\u00eb shp\u00ebrndara n\u00eb labirint. Idealisht, labirinti duhet t\u00eb jet\u00eb sa m\u00eb i gjat\u00eb t\u00eb jet\u00eb e mundur, p\u00ebr t\u00eb pasur koh\u00eb p\u00ebr t'u shkaktuar monstruoz\u00ebve nj\u00eb sasi t\u00eb mjaftueshme d\u00ebmi dhe p\u00ebr t\u00eb mos u lejuar atyre t\u00eb arrijn\u00eb kull\u00ebn. P\u00ebr disa lloje arm\u00ebsh, monstruoz\u00ebt jan\u00eb m\u00eb t\u00eb ndjesh\u00ebm sesa p\u00ebr t\u00eb tjerat, prandaj p\u00ebr nj\u00eb efikasitet m\u00eb t\u00eb madh, vlen t'i vendosni ato n\u00eb labirint para t\u00eb tjerave. Karakteristika e Unleash q\u00ebndron n\u00eb faktin se nuk ekziston nj\u00eb labirint ideal: n\u00eb loj\u00eb ka kaq shum\u00eb lloje monstruoz\u00ebsh, saq\u00eb ndonj\u00eb nga ata do t\u00eb kaloj\u00eb pa pengesa p\u00ebrmes ndonj\u00eb segmenti t\u00eb labirintit. \u00c7do labirint duhet t\u00eb adaptohet p\u00ebr monstrat e rinj, q\u00eb l\u00ebshohen nga lojtar\u00eb t\u00eb tjer\u00eb. K\u00ebshtu, ishte e nevojshme jo vet\u00ebm t\u00eb m\u00ebsohej inteligjenca artificiale t\u00eb nd\u00ebrtoj\u00eb labirintet \u2014 ishte e nevojshme t'i m\u00ebsohej asaj t\u00eb krijonte labirinte efektive p\u00ebr skenar\u00eb t\u00eb ndrysh\u00ebm, me t\u00eb cilat mund t\u00eb p\u00ebrballeshin si n\u00eb versionin e hersh\u00ebm ashtu edhe n\u00eb at\u00eb t\u00eb von\u00eb t\u00eb loj\u00ebs. <\/p>\n

Po ashtu, AI duhet t\u00eb kishte m\u00ebsuar t\u00eb llogariste se cil\u00ebt monstruoz\u00eb do t\u00eb shfaqeshin n\u00eb labirint. Kjo \u00ebsht\u00eb nj\u00eb lloj problemi t\u00ebrthor n\u00eb lidhje me nd\u00ebrtimin e labirintit. Si n\u00eb shum\u00eb loj\u00ebra t\u00eb tjera, n\u00eb Unleash nuk mjafton thjesht t\u00eb rrit\u00ebsh ushtrin\u00eb dhe ta d\u00ebrgosh at\u00eb n\u00eb vendin e armikut: \u00ebsht\u00eb gjithashtu e nevojshme q\u00eb t\u00eb spiunosh mbrojtjen armike dhe t\u00eb strukturosh ushtrin\u00eb n\u00eb m\u00ebnyr\u00eb q\u00eb t\u00eb godas\u00ebsh sa m\u00eb efektivisht pika t\u00eb ndjeshme t\u00eb kund\u00ebrshtarit. Ushtria e monstruoz\u00ebve duhet t\u00eb bashk\u00ebpunoj\u00eb n\u00eb m\u00ebnyr\u00eb q\u00eb t\u00eb dep\u00ebrtoj\u00eb me sukses p\u00ebrmes labirintit. Ndonj\u00ebher\u00eb \u00ebsht\u00eb gjithashtu e nevojshme t\u00eb l\u00ebshohen monstruoz\u00ebt n\u00eb nj\u00eb renditje t\u00eb caktuar n\u00eb var\u00ebsi t\u00eb funksioneve dhe rolit t\u00eb tyre. Kjo gjithashtu rrit numrin e kombinimeve t\u00eb ndryshme.<\/p>\n

N\u00eb fund, nd\u00ebrsa lojtari duhet t\u00eb krijoj\u00eb labirinte dhe t\u00eb grumbulloj\u00eb nj\u00eb ushtri monstruoz\u00ebsh, AI gjithashtu duhet t\u00eb m\u00ebsoj\u00eb t\u00eb gjej\u00eb balanc\u00ebn midis sulmit dhe mbrojtjes. Gjithashtu, duhet t\u00eb merret parasysh se sa m\u00eb shum\u00eb q\u00eb lojtari t\u00eb rris\u00eb ushtrin\u00eb e monstruoz\u00ebve dhe sa m\u00eb shum\u00eb t\u00eb nd\u00ebrtoj\u00eb labirentin, aq m\u00eb shum\u00eb burime i nevojiten p\u00ebr k\u00ebt\u00eb. Prandaj, nj\u00eb strategji e duhur sulmi \u00ebsht\u00eb jasht\u00ebzakonisht e r\u00ebnd\u00ebsishme si p\u00ebr ekonomin\u00eb gjat\u00eb loj\u00ebs ashtu edhe p\u00ebr fitore n\u00eb t\u00eb. P\u00ebr t\u00eb siguruar konkurrenc\u00ebn, AI duhet t\u00eb dij\u00eb si t\u00eb menaxhoj\u00eb burimet n\u00eb m\u00ebnyr\u00eb q\u00eb t\u00eb krijoj\u00eb nj\u00eb ushtri t\u00eb fuqishme monstruoz\u00ebsh pa v\u00ebn\u00eb n\u00eb rrezik forc\u00ebn e labirintit. Investimi maksimal n\u00eb monstruoz\u00eb mund t\u00eb jet\u00eb ekonomikisht fitimprur\u00ebs, por rrit rrezikun e kapjes s\u00eb labirintit nga monstruoz\u00ebt e kund\u00ebrshtarit. N\u00ebse b\u00ebni bast n\u00eb forcimin e mbrojtjes s\u00eb labirintit, kjo mund t\u00eb d\u00ebmtoj\u00eb ekonomin\u00eb tuaj. Asnj\u00ebra nga k\u00ebto skenar\u00eb nuk do t\u00eb \u00e7oj\u00eb n\u00eb fitore. K\u00ebshtu, problemi i optimizimit n\u00eb Unleashed rezulton t\u00eb jet\u00eb m\u00eb kompleks se n\u00eb rastin e shahut ose Starcraft dhe p\u00ebrfshin nevoj\u00ebn p\u00ebr t\u00eb sakrifikuar di\u00e7ka dhe p\u00ebr t\u00eb llogaritur p\u00ebrfitimin tuaj disa hapa p\u00ebrpara. <\/p>\n

Gjat\u00eb trajnimit t\u00eb inteligjenc\u00ebs artificiale shfaqen shum\u00eb probleme q\u00eb nuk ishin marr\u00eb parasysh m\u00eb par\u00eb. N\u00eb fillim, AI shpesh arrinte nj\u00eb nivel t\u00eb caktuar zhvillimi, n\u00eb t\u00eb cilin fillonte t\u00eb kuptonte disa aspekte t\u00eb loj\u00ebs \u2014 p\u00ebr shembull, cilat arme n\u00eb labirint jan\u00eb efektive kund\u00ebr llojeve t\u00eb caktuara t\u00eb monstruoz\u00ebve ose cil\u00ebt monstruoz\u00eb kalojn\u00eb m\u00eb mir\u00eb n\u00eb disa pjes\u00eb t\u00eb labirintit. Por trajnimi ishte i ngadalsh\u00ebm dhe \u00e7onte n\u00eb zhvillimin e strategjive t\u00eb ngjashme. <\/p>\n

<\/p>\n

Nevoja p\u00ebr qasje paralele<\/h3>\n

\nNd\u00ebrsa trajnimi i inteligjenc\u00ebs artificiale t\u00eb bazuar n\u00eb m\u00ebsimin e makinerive u zhvillua ngadal\u00eb dhe nuk ishte shum\u00eb i suksessh\u00ebm, p\u00ebr faza t\u00eb tjera t\u00eb testimit dhe zhvillimit u b\u00eb e nevojshme nj\u00eb inteligjenc\u00eb artificiale m\u00eb e mir\u00eb dhe inteligjenc\u00eb konkurruese m\u00eb t\u00eb besueshme. P\u00ebr realizimin e tyre u p\u00ebrdor arkitektura Utility, me an\u00eb t\u00eb s\u00eb cil\u00ebs mund t\u00eb krijohen inteligjenca artificiale specifike p\u00ebr testimin dhe verifikimin e cil\u00ebsis\u00eb s\u00eb loj\u00ebs, teste t\u00eb brendshme t\u00eb loj\u00ebs dhe balancimin e arm\u00ebve dhe monsterave, si dhe krijimin e labirinteve dhe monsterave specifik\u00eb. Megjithat\u00eb, gjat\u00eb zhvillimit t\u00eb Unleash, krijuesit vet\u00eb shp\u00ebrblenin aft\u00ebsit\u00eb e tyre n\u00eb kalimin e saj, dhe m\u00eb pas vendos\u00ebn t\u00eb p\u00ebrdorin njohurit\u00eb e marra p\u00ebr t\u00eb krijuar nj\u00eb inteligjenc\u00eb Utility m\u00eb t\u00eb avancuar. K\u00ebshtu u b\u00eb e qart\u00eb se shum\u00eb prej problemeve q\u00eb paraqiten n\u00eb sistemet e inteligjenc\u00ebs artificiale t\u00eb bazuara n\u00eb m\u00ebsimin e makinerive mund t\u00eb zgjidhen leht\u00ebsisht me an\u00eb t\u00eb sistemeve Utility q\u00eb p\u00ebrdorin njohurit\u00eb e integruara n\u00eb to, dhe anasjelltas. <\/p>\n

P\u00ebr shembull, labirintet m\u00eb efikase mund t\u00eb nd\u00ebrtohen m\u00eb mir\u00eb me ndihm\u00ebn e inteligjenc\u00ebs Utility q\u00eb bazohet n\u00eb bazat e njohurive t\u00eb mbledhura nga rezultatet e testeve t\u00eb brendshme. \u00cbsht\u00eb e leht\u00eb t\u00eb p\u00ebrshkruash dhe programosh nj\u00eb algorit\u00ebm p\u00ebr nd\u00ebrtimin e labirintit dhe vendosjen e arm\u00ebve n\u00eb t\u00eb nj\u00eb m\u00ebnyr\u00eb, si\u00e7 do t\u00eb ishte m\u00eb e leht\u00eb p\u00ebr nj\u00eb lojtar t\u00eb mbroj\u00eb nj\u00eb kull\u00eb nga monsterat specifik\u00eb. Nd\u00ebrsa krijimi i nj\u00eb arme monsterash mbi baz\u00ebn e njohurive mbi baz\u00ebn e armikut paraqiti nj\u00eb sfid\u00eb t\u00eb v\u00ebshtir\u00eb p\u00ebr k\u00ebta inteligjenca, pasi numri i kushteve dhe kombinimeve t\u00eb ndryshme q\u00eb duhej t\u00eb merreshin parasysh ishte marramend\u00ebs. Me nj\u00eb lloj t\u00eb till\u00eb arkitekture, k\u00ebrkimi i grupeve t\u00eb p\u00ebrshtatshme t\u00eb monsterave do t\u00eb zinte nj\u00eb koh\u00eb t\u00eb pafund. At\u00ebher\u00eb, me kushtet e caktuara t\u00eb dh\u00ebna, m\u00ebsimi i thell\u00eb do t\u00eb ishte zgjidhja ideale p\u00ebr k\u00ebt\u00eb problem. <\/p>\n

<\/p>\n

Krijimi i inteligjencave hibride<\/h3>\n

\nPra ndaj, u vendos t\u00eb kombinohen dy qasje dhe k\u00ebshtu t\u00eb krijohet nj\u00eb sistem hibrid i inteligjenc\u00ebs artificiale i bazuar n\u00eb m\u00ebsimin e maqinerive dhe Utility. Ideja ishte se, atje ku ishte e nevojshme t\u00eb p\u00ebrpunoheshin nj\u00eb sasi t\u00eb madhe kombinimesh dhe gjendjesh t\u00eb loj\u00ebs, ose ku k\u00ebrkohej t\u00eb m\u00ebsohej di\u00e7ka, p\u00ebrdorej m\u00ebsimi i maqinerive. P\u00ebr detyra t\u00eb tjera, ku ishte m\u00eb mir\u00eb t\u00eb mb\u00ebshteteshim n\u00eb p\u00ebrvoj\u00ebn personale t\u00eb zhvilluesve, u angazhuan sistemet Utility. Avantazhi i k\u00ebsaj qasje \u00ebsht\u00eb gjithashtu se, n\u00ebse \u00ebsht\u00eb e nevojshme, mund t\u00eb kontrollohet m\u00eb mir\u00eb sjellja e IA-s p\u00ebr t\u00eb siguruar nj\u00eb ndjekje m\u00eb t\u00eb sakt\u00eb t\u00eb q\u00ebllimit t\u00eb caktuar. P\u00ebr shembull, mund t\u00eb p\u00ebrdorim IA Utility p\u00ebr t\u00eb siguruar nj\u00eb balanc\u00eb midis sulmit dhe mbrojtjes dhe k\u00ebshtu t\u00eb krijojm\u00eb nivele t\u00eb ndryshme agresiviteti, ose mund t\u00eb krijojm\u00eb konfiguracione t\u00eb ndryshme t\u00eb labirinteve p\u00ebr IA t\u00eb ndryshme, p\u00ebr t'u formuar atyre stile t\u00eb ve\u00e7anta loje. Po ashtu, mund t'u caktom\u00ebmi rrjeteve nervore sisteme t\u00eb caktuara vlerash p\u00ebr formimin e preferencave t\u00eb ndryshme gjat\u00eb zgjedhjes s\u00eb monstave ajrore ose tok\u00ebsore dhe k\u00ebshtu gjithashtu t\u00eb shtojm\u00eb individualitet p\u00ebr IA t\u00eb ve\u00e7anta. Ka ende shum\u00eb opsione t\u00eb tjera p\u00ebr realizimin e zgjidhjeve t\u00eb projektit, dhe t\u00eb gjitha theksojn\u00eb pikat e forta t\u00eb llojeve t\u00eb ndryshme t\u00eb arkitektur\u00ebs s\u00eb IA-s. <\/p>\n

Qasja hibride gjithashtu ishte p\u00ebrgjigje ndaj nj\u00eb pyetjeje tjet\u00ebr q\u00eb i ishte paraqitur ekipit t\u00eb zhvilluesve gjat\u00eb procesit t\u00eb zhvillimit t\u00eb inteligjenc\u00ebs artificiale p\u00ebr Unleash: a duhet t\u00eb aplikohet nj\u00eb rrjet i thell\u00eb global i vet\u00ebm i bazuar n\u00eb m\u00ebsimin e maqinerive p\u00ebr t\u00eb marr\u00eb parasysh t\u00eb gjitha t\u00eb dh\u00ebnat hyr\u00ebse dhe dal\u00ebse, apo \u00ebsht\u00eb m\u00eb mir\u00eb t\u00eb projektohet IA me nj\u00eb struktur\u00eb hierarkike? <\/p>\n

\"Si
\nDy arkitektura q\u00eb jan\u00eb p\u00ebrdorur n\u00eb Unleash: majtas \u2014 nj\u00eb rrjet i madh i thell\u00eb me nj\u00eb arkitektur\u00eb t\u00eb vetme, djathtas \u2014 nj\u00eb sistem hierarkik, ku secila rrjet ka detyr\u00ebn e saj.<\/i><\/p>\n

Megjithat\u00eb, do t\u00eb d\u00ebshironim t\u00eb krijonim nj\u00eb qasje t\u00eb p\u00ebrbashk\u00ebt p\u00ebr sistemin e inteligjenc\u00ebs artificiale, n\u00eb arkitektur\u00ebn e t\u00eb cilit zhvilluesit nuk do t\u00eb integronin p\u00ebrvoj\u00ebn e tyre. Megjithat\u00eb, sa m\u00eb shum\u00eb her\u00eb q\u00eb hynte n\u00eb loj\u00eb, aq m\u00eb shum\u00eb rritej rrjeti nervor. N\u00eb k\u00ebt\u00eb m\u00ebnyr\u00eb, nuk ishte e mundur t\u00eb ndaheshin trajnimi i AI-s\u00eb dhe t\u00eb m\u00ebsonin di\u00e7ka t\u00eb vetme: ose mbrojtje, ose sulm. Dhe u shfaq\u00ebn shqet\u00ebsime se nj\u00eb qasje m\u00eb e p\u00ebrgjithshme do t\u00eb kishte nj\u00eb rritje t\u00eb konsiderueshme t\u00eb numrit t\u00eb llogaritjeve. <\/p>\n

Prej k\u00ebtej lindi ideja p\u00ebr t\u00eb krijuar nj\u00eb arkitektur\u00eb hierarkike, n\u00eb t\u00eb cil\u00ebn \u00e7do detyr\u00eb specifike do t\u00eb kryhej nga nj\u00eb rrjet nervor i specializuar. Sipas k\u00ebsaj ideje, fillimisht inteligjenca artificiale duhet t\u00eb marr\u00eb nj\u00eb vendim p\u00ebr shp\u00ebrndarjen e burimeve n\u00eb sulm (rritja e ushtris\u00eb s\u00eb monstruzve) dhe mbrojtje (nd\u00ebrtimi i labirintit). Pas vendimmarrjes, ajo kalon n\u00eb shtres\u00ebn tjet\u00ebr sipas zgjedhjes s\u00eb saj dhe merr akses n\u00eb pjes\u00ebn e nevojshme t\u00eb gjendjes s\u00eb loj\u00ebs, pas s\u00eb cil\u00ebs merr vendime t\u00eb detajuara p\u00ebr cil\u00ebt monstruz\u00eb t\u00eb zgjedh\u00eb dhe \u00e7far\u00eb arme t\u00eb vendos\u00eb n\u00eb labirint.<\/p>\n

<\/p>\n

P\u00ebrfundimi dhe hapat e ardhsh\u00ebm<\/h3>\n

\nMe qasjen hibride, Utility AI me rrjetet e tij t\u00eb integruara n\u00eb baz\u00eb t\u00eb t\u00eb m\u00ebsuarit t\u00eb makinerive ngjason me arkitektur\u00ebn hierarkike. Kjo e fundit, nga ana tjet\u00ebr, \u00ebsht\u00eb e ngjashme me trurin biologjik, ku qendrat e ndryshme nervore p\u00ebrgjigjen secila p\u00ebr detyrat e veta.<\/p>\n

Aktualisht, AI i armikut n\u00eb Unleash \u00ebsht\u00eb shum\u00eb e v\u00ebshtir\u00eb p\u00ebr tu mundur: ata jan\u00eb n\u00eb gjendje t\u00eb p\u00ebrshtaten me \u00e7do situat\u00eb n\u00eb loj\u00eb, \u2013 por zhvilluesit mund t\u00eb ndryshojn\u00eb cil\u00ebsimet e tyre sipas d\u00ebshires. Sipas mendimit t\u00eb autorit t\u00eb artikullit, me kalimin e koh\u00ebs qasja hibride duhet t\u00eb b\u00ebj\u00eb m\u00eb shum\u00eb p\u00ebrhapje dhe t\u00eb shfaqet n\u00eb shum\u00eb loj\u00ebra t\u00eb tjera. Ndoshta, ndonj\u00ebher\u00eb do t\u00eb jet\u00eb e mundur t\u00eb integrohet inteligjenca artificiale e bazuar n\u00eb t\u00eb m\u00ebsuarin e makinerive n\u00eb m\u00ebnyr\u00eb t\u00eb past\u00ebr n\u00eb procesin e loj\u00ebs. Por, sigurisht, p\u00ebr k\u00ebt\u00eb do t\u00eb nevojitet ende koh\u00eb. Nd\u00ebrkoh\u00eb, q\u00ebllimi \u00ebsht\u00eb t\u00eb gjejm\u00eb nj\u00eb arkitektur\u00eb, e cila do t\u00eb p\u00ebrshtatet vet\u00eb me detyrat q\u00eb ka p\u00ebrpara dhe do t\u00eb gjej\u00eb m\u00ebnyrat optimale p\u00ebr t'i zgjidhur ato.
\n
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