- Tytuł:
- Multi agent deep learning with cooperative communication
- Autorzy:
-
Simões, David
Lau, Nuno
Reis, Luís Paulo - Powiązania:
- https://bibliotekanauki.pl/articles/1837537.pdf
- Data publikacji:
- 2020
- Wydawca:
- Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
- Tematy:
-
multi-agent systems
deep reinforcement learning
centralized learning - Opis:
- We consider the problem of multi agents cooperating in a partially-observable environment. Agents must learn to coordinate and share relevant information to solve the tasks successfully. This article describes Asynchronous Advantage Actor-Critic with Communication (A3C2), an end-to-end differentiable approach where agents learn policies and communication protocols simultaneously. A3C2 uses a centralized learning, distributed execution paradigm, supports independent agents, dynamic team sizes, partiallyobservable environments, and noisy communications. We compare and show that A3C2 outperforms other state-of-the-art proposals in multiple environments.
- Źródło:
-
Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 3; 189-207
2083-2567
2449-6499 - Pojawia się w:
- Journal of Artificial Intelligence and Soft Computing Research
- Dostawca treści:
- Biblioteka Nauki
Artykuł