Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 100808-100830 |
| Seitenumfang | 23 |
| Fachzeitschrift | IEEE ACCESS |
| Jahrgang | 13 |
| Publikationsstatus | Veröffentlicht - 22 Mai 2025 |
Abstract
Abstraction techniques play a crucial role in enabling agents to make decisions more effectively by simplifying complex problems. This survey provides a comprehensive literature overview of non-learned abstraction construction methods and explores how these abstractions can enhance or be seamlessly integrated into existing solvers. We delve into key properties of abstractions, outline general strategies for constructing them, and discuss specialized approaches for specific problem domains, such as those with continuous action spaces. Additionally, we introduce the Abstraction Mapping Graph (AMG) framework, offering a structured lens through which abstraction usage can be systematically understood.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Allgemeine Computerwissenschaft
- Werkstoffwissenschaften (insg.)
- Allgemeine Materialwissenschaften
- Ingenieurwesen (insg.)
- Allgemeiner Maschinenbau
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in: IEEE ACCESS, Jahrgang 13, 22.05.2025, S. 100808-100830.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - A Survey of Non-Learning-Based Abstractions for Sequential Decision-Making
AU - Schmöcker, Robin
AU - Dockhorn, Alexander
N1 - Publisher Copyright: © 2013 IEEE.
PY - 2025/5/22
Y1 - 2025/5/22
N2 - Abstraction techniques play a crucial role in enabling agents to make decisions more effectively by simplifying complex problems. This survey provides a comprehensive literature overview of non-learned abstraction construction methods and explores how these abstractions can enhance or be seamlessly integrated into existing solvers. We delve into key properties of abstractions, outline general strategies for constructing them, and discuss specialized approaches for specific problem domains, such as those with continuous action spaces. Additionally, we introduce the Abstraction Mapping Graph (AMG) framework, offering a structured lens through which abstraction usage can be systematically understood.
AB - Abstraction techniques play a crucial role in enabling agents to make decisions more effectively by simplifying complex problems. This survey provides a comprehensive literature overview of non-learned abstraction construction methods and explores how these abstractions can enhance or be seamlessly integrated into existing solvers. We delve into key properties of abstractions, outline general strategies for constructing them, and discuss specialized approaches for specific problem domains, such as those with continuous action spaces. Additionally, we introduce the Abstraction Mapping Graph (AMG) framework, offering a structured lens through which abstraction usage can be systematically understood.
KW - Abstractions
KW - artificial intelligence
KW - sequential decision-making
UR - http://www.scopus.com/inward/record.url?scp=105006761183&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2025.3572830
DO - 10.1109/ACCESS.2025.3572830
M3 - Article
AN - SCOPUS:105006761183
VL - 13
SP - 100808
EP - 100830
JO - IEEE ACCESS
JF - IEEE ACCESS
SN - 2169-3536
ER -