Mašinsko učenje
Mašinsko učenje je podoblast vještačke inteligencije čiji je cilj konstruisanje algoritama i računarskih sistema koji su sposobni da se adaptiraju na analogne nove situacije i uče na bazi iskustva. Razvijene su različite tehnike učenja za izvršavanje različitih zadataka. Prve koje su bile predmet istraživanja, tiču se nadgledanog učenja za diskreciono donošenje odluka, nadgledanog učenja za kontinuirano predviđanje i pojačano učenje za sekvencionalno donošenje odluka, kao i nenadgledano učenje.
Do sada najbolje shvaćen od svih navedenih zadataka je odlučivanje preko jednog pokušaja (engl. one-shot learning). Računaru je dat opis jednog objekta (događaja ili situacije) i od njega se očekuje da kao rezultat izbaci klasifikaciju tog objekta. Na primjer, program za prepoznavanje alfanumeričkih znakova kao ulaznu vrijednost ima digitalizovanu sliku nekog alfanumeričkog znaka i kao rezultat treba da izbaci njegovo ime.
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