A Bayesian model for RTS units control applied to StarCraft

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Episodic Exploration for Deep Deterministic Policies: An Application to StarCraft Micromanagement Tasks (2016, background): “…implies, in particular, extremely large state and action spaces: in a typical game, there are at least 10 1685 possible states (for reference, the game of Go has about 10 170 states) and the joint action space is in Θ((# commands per unit ) # units ) , with a peak number of units of about 400 [36].”
MOBA: a New Arena for Game AI (2017, background): “Problems like unit management [15], tactical gameplay [5], kiting [16], among others, were extensively studied in the RTS environment.”
A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft (2013, unknown): “3 shows some representative examples of the architectures used by different bots in the AIIDE and CIG StarCraft AI competitions (see Section V): BroodwarBotQ [50], Nova”
A Review of Real-Time Strategy Game AI (2014, methodology): “…area of AI research, RTS games present a huge increase in complexity – at least an order of magnitude increase in the number of possible game states, actions to choose from, actions per game, and actions per minute (using standard rules) (Buro 2004; Schaeffer 2001; Synnaeve andBessì ere 2011b).”