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Game Theoretic Learning and Distributed Optimization in Memoryless Multi Agent S Tatarenko 1st ed. 2017 edition
Game Theoretic Learning and Distributed Optimization in Memoryless Multi Agent S
Tatarenko
These methods do not require the agents to have the full information about the system, but instead allow them to make their local decisions based only on the local information, possibly obtained during communication with their local neighbors.
171 pages, 38 Tables, color; 38 Illustrations, black and white; IX, 171 p. 38 illus.
| Médias | Livres Book |
| Validé | 28 septembre 2017 |
| ISBN13 | 9783319654782 |
| Éditeurs | Springer International Publishing AG |
| Pages | 171 |
| Dimensions | 150 × 220 × 20 mm · 435 g |
| Langue et grammaire | Allemand |