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- W4297789503 abstract "Relational representations in reinforcement learning allow for the use of structural information like the presence of objects and relationships between them in the description of value functions. Through this paper, we show that such representations allow for the inclusion of background knowledge that qualitatively describes a state and can be used to design agents that demonstrate learning behavior in domains with large state and actions spaces such as computer games." @default.
- W4297789503 created "2022-10-01" @default.
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- W4297789503 date "2012-02-28" @default.
- W4297789503 modified "2023-09-25" @default.
- W4297789503 title "Relational Reinforcement Learning in Infinite Mario" @default.
- W4297789503 doi "https://doi.org/10.48550/arxiv.1202.6386" @default.
- W4297789503 hasPublicationYear "2012" @default.
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