Multi-scale Bayesian modeling for RTS games: an application to StarCraft AIReportar como inadecuado




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1 LSCP - Laboratoire de sciences cognitives et psycholinguistique 2 LPPA - Laboratoire de Physiologie de la Perception et de l-Action

Abstract : This paper showcases the use of Bayesian models for real-time strategy RTS games AI in three distinct core components: micro-management units control, tactics army moves and positions, and strategy economy, technology, production, army types. The strength of having end-to-end probabilisticmodels is that distributions on specific variables can be used to inter-connect different models at different levels of abstraction.We applied this modeling to StarCraft, and evaluated each model independently. Along the way, we produced and released a comprehensive dataset for RTS machine learning.

Keywords : StarCraft video games RTS AI real-time strategy Bayesian modeling tactics micro-management





Autor: Gabriel Synnaeve - Pierre Bessiere -

Fuente: https://hal.archives-ouvertes.fr/



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