Abstract
| Original language | English |
|---|---|
| Title of host publication | 2019 IEEE Conference on Games (CoG) |
| Publisher | IEEE |
| Number of pages | 8 |
| ISBN (Electronic) | 978-1-7281-1884-0 |
| ISBN (Print) | 978-1-7281-1885-7 |
| DOIs | |
| Publication status | Published - 26 Sep 2019 |
Publication series
| Name | |
|---|---|
| ISSN (Print) | 2325-4270 |
| ISSN (Electronic) | 2325-4289 |
Fingerprint
Keywords
- GVGAI
- GVGP
- Ensemble Decision Systems
- Game AI
Cite this
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Ensemble decision systems for general video game playing. / Anderson, Damien; Rodgers, Philip; Levine, John; Guerrero-Romero, Cristina; Perez-Liebana, Diego.
2019 IEEE Conference on Games (CoG). IEEE, 2019.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Ensemble decision systems for general video game playing
AU - Anderson, Damien
AU - Rodgers, Philip
AU - Levine, John
AU - Guerrero-Romero, Cristina
AU - Perez-Liebana, Diego
N1 - Acceptance in SAN (author confirmed this is the acceptance confirmation). ET 13/2/20 Changed template to proceedings ET 10/2/20 AAM: no embargo - found copy via Unpaywall and uploaded. ET 10/2/20 In REF policy scope - paper has ISSN. ET
PY - 2019/9/26
Y1 - 2019/9/26
N2 - Ensemble Decision Systems offer a unique form of decision making that allows a collection of algorithms to reason together about a problem. Each individual algorithm has its own inherent strengths and weaknesses, and often it is difficult to overcome the weaknesses, while retaining the strengths. Instead of altering the properties of the algorithm, the Ensemble Decision System augments the performance with other algorithms that have complementing strengths. This work outlines different options for building an Ensemble Decision System as well as providing analysis on its performance compared to the individual components of the system with interesting results, showing an increase in the generality of the algorithms without significantly impeding performance.
AB - Ensemble Decision Systems offer a unique form of decision making that allows a collection of algorithms to reason together about a problem. Each individual algorithm has its own inherent strengths and weaknesses, and often it is difficult to overcome the weaknesses, while retaining the strengths. Instead of altering the properties of the algorithm, the Ensemble Decision System augments the performance with other algorithms that have complementing strengths. This work outlines different options for building an Ensemble Decision System as well as providing analysis on its performance compared to the individual components of the system with interesting results, showing an increase in the generality of the algorithms without significantly impeding performance.
KW - GVGAI
KW - GVGP
KW - Ensemble Decision Systems
KW - Game AI
U2 - 10.1109/CIG.2019.8848089
DO - 10.1109/CIG.2019.8848089
M3 - Conference contribution
SN - 978-1-7281-1885-7
BT - 2019 IEEE Conference on Games (CoG)
PB - IEEE
ER -