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3 Annals of Computer Science and Information Systems

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StarCraft agent strategic training on a large human versus human game replay dataset

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Krištofík Š. , Malík P. , Kasáš M. , Neupauer Š.

Annals of Computer Science and Information Systems

2020

tom Vol. 21

391--399

Real-time strategy games are currently very popular as a testbed for AI research and education. StarCraft: Brood War (SC:BW) is one of such games. Recently, a new large, unlabeled human versus human SC:BW game replay dataset called STARDATA was published. This paper aims to prove that the player strategy diversity requirement of the dataset is met, i.e., that the diversity of player strategies in STARDATA replays is of sufficient quality. To this end, we built a competitive SC:BW agent from scratch and trained its strategic decision making process on STARDATA. The results show that in the current state of the competitive environment the agent is capable of keeping a stable rating and a decent win rate over a longer period of time. It also performs better than our other, simple rule-based agent. Therefore, we conclude that the strategy diversity requirement of STARDATA is met.

Instance Segmentation Model Created from Three Semantic Segmentations of Mask, Boundary and Centroid Pixels Verified on GlaS Dataset

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Malík P. , Krištofík Š. , Knapová K.

Annals of Computer Science and Information Systems

2020

tom Vol. 21

569--576

Segmentation is the key computer vision task in modern medicine applications. Instance segmentation became the prevalent way to improve segmentation performance in recent years. This work proposes a novel way to design an instance segmentation model that combines 3 semantic segmentation models dedicated for foreground, boundary and centroid predictions. It contains no detector so it is orthogonal to a standard instance segmentation design and can be used to improve the performance of a standard design. The presented custom designed model is verified on the Gland Segmentation in Colon Histology Images dataset.

StarCraft Strategy Classification of a Large Human versus Human Game Replay Dataset

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Krištofík Š. , Malík P. , Kasáš M.

Annals of Computer Science and Information Systems

2021

tom Vol. 25

137--140

Real-time strategy games are popular in AI research and education. Among them, Starcraft: Brood War (SCBW) is particularly well known. Recently, the largest known SCBW game replay dataset STARDATA was published. We classify player strategies used in the dataset for all 3 playable races and all 6 match-ups. We focus on early to mid-game strategies in matches less than 15 minutes long. By mapping the classified strategies to replay files, we label the files of the dataset and make the labeled dataset available.