Kong et al., 2020 - Google Patents
Multi-ucav air combat in short-range maneuver strategy generation using reinforcement learning and curriculum learningKong et al., 2020
- Document ID
- 18070352368797794357
- Author
- Kong W
- Zhou D
- Zhang K
- Yang Z
- Yang W
- Publication year
- Publication venue
- 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA)
External Links
Snippet
We present an approach for learning a reactive maneuver strategy for a UCAV formation involved in a short-range multi-UCAV air combat engagement. Specifically, we define an efficient state representation, which breaks down the complexity caused by the large state …
- 230000002787 reinforcement 0 title description 9
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/08—Learning methods
- G06N3/082—Learning methods modifying the architecture, e.g. adding or deleting nodes or connections, pruning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
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