Using Machine Learning in SC2

Tereso del Río

Using Machine Learning in SC2

Research Centre for Computational Science and Mathematical Modelling

Research output: Contribution to conference › Other

Abstract

This talk exposes many possible uses of Machine Learning (ML) in the context of SC2, and how this approach differs from human-made heuristics. Different ML paradigms are presented and it is discussed how symbolic data could be encoded. This talk also intends to motivate a discussion about which datasets should be used for training and testing ML models.

Original language	English
Publication status	Published - 23 Aug 2022
Event	Dagstuhl Seminar 22072 - Duration: 13 Feb 2022 → 18 Feb 2022

Conference

Conference	Dagstuhl Seminar 22072
Period	13/02/22 → 18/02/22

Cite this

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title = "Using Machine Learning in SC2",

abstract = "This talk exposes many possible uses of Machine Learning (ML) in the context of SC2, and how this approach differs from human-made heuristics. Different ML paradigms are presented and it is discussed how symbolic data could be encoded. This talk also intends to motivate a discussion about which datasets should be used for training and testing ML models.",

author = "{del R{\'i}o}, Tereso",

year = "2022",

month = aug,

day = "23",

language = "English",

note = "Dagstuhl Seminar 22072 ; Conference date: 13-02-2022 Through 18-02-2022",

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TY - CONF

T1 - Using Machine Learning in SC2

AU - del Río, Tereso

PY - 2022/8/23

Y1 - 2022/8/23

N2 - This talk exposes many possible uses of Machine Learning (ML) in the context of SC2, and how this approach differs from human-made heuristics. Different ML paradigms are presented and it is discussed how symbolic data could be encoded. This talk also intends to motivate a discussion about which datasets should be used for training and testing ML models.

AB - This talk exposes many possible uses of Machine Learning (ML) in the context of SC2, and how this approach differs from human-made heuristics. Different ML paradigms are presented and it is discussed how symbolic data could be encoded. This talk also intends to motivate a discussion about which datasets should be used for training and testing ML models.

M3 - Other

T2 - Dagstuhl Seminar 22072

Y2 - 13 February 2022 through 18 February 2022

ER -

Using Machine Learning in SC2

Abstract

Conference

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