Software agent-based applications, platforms and development kits
By R. Unland, Matthias Klusch, M. Calisti. 2005
98 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Shimon Whiteson
- Jakob N. Foerster
- Philip H. S. Torr
- Gregory Farquhar
- Chongjie Zhang
- Tonghan Wang
- Christian Schröder de Witt
- Wendelin Böhmer
In Computer Networks and Communications
- Gregory Farquhar
- Philip H. S. Torr
- Pushmeet Kohli
- Jakob N. Foerster
- Shimon Whiteson
- Nantas Nardelli
- Aadirupa Saha
- Masrour Zoghi
Citations in the corpus
- Counterfactual Multi-Agent Policy Gradients (2017, neutral): “Many simpler multi-agent settings, such as Predator-Prey (Tan, 1993) or Packet World (Weyns et al., 2005), by contrast, have full simulators with controlled randomness that can be freely set to any state in order to perfectly replay experiences.”
- Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning (2017, methodology): “This differs from standard multi-agent settings such as Packet World (Weyns et al., 2005) and simulated RoboCup (Hausknecht et al.”