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type: Thesis
acceptance date: 2023-01-17
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creation year: 2006
description: Rozprawa rozpatruje zagadnienia związane z problemem sterowania na przykładzie gry w anty-warcaby, a celem jest stworzenie algorytmu uczącego się w nie grać. Wykorzystano tu znany algorytm uczenia ze wzmocnieniem -- Temporal Difference TD(λ) który można stosować w sytuacji gdy ocena pracy agenta następuje dopiero po zakończeniu rozgrywki i znany jest jej wynik. Ważnym elementem wpływającym na skuteczność algorytmu uczącego był odpowiedni dobór strategii treningowej, co zostało szczegółowo opisane. W pracy został również wykorzystany algorytm pseudo-ewolucyjny EVO, którego zastosowanie umożliwiło porównanie skuteczności algorytmu TD(λ) z odmienną metodą nauczania taktyki agenta. Algorytm został zaimplementowany i przetestowany w języku Ocaml.
destination group: naukowcy
destination group: uczniowie
destination group: studenci
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language: Polski
number of pages: 121
origin: AZON2
place of creation: Warszawa
scientific discipline: Dziedzina nauk inżynieryjno-technicznych / informatyka techniczna i telekomunikacja (2018)
supervisor: http://id.e-science.pl/vocab/person/10327
title: Skuteczość metod uczenia w algorytmach z rodziny Temporal Difference w zastosowaniu do dwuoosobowych gier planszowych (PD-2007-04)

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