Coordination of communication in robot teams by reinforcement learning

By Darío Maravall Gómez-Allende, Javier de Lope Asiaín, Raúl Domínguez. 2011

32 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cultural Studies, Sociology and Political Science

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

1. Shimon Whiteson
2. Jakob N. Foerster
3. Sergey Levine
4. Pieter Abbeel
5. Yoshua Bengio
6. Arthur Szlam
7. Mohit Bansal
8. Kyunghyun Cho

In Cultural Studies

1. Nando de Freitas
2. Shimon Whiteson
3. Sainbayar Sukhbaatar
4. Rob Fergus
5. Arthur Szlam

In Sociology and Political Science

1. Arthur Szlam
2. Rob Fergus
3. Sainbayar Sukhbaatar
4. Shimon Whiteson
5. Jakob N. Foerster

Citations in the corpus

• Learning Multiagent Communication with Backpropagation (2016, methodology): “Others use co unic ti n, but with a p -d rmin d p otoc l [30, 19, 37, 17].”
• Learning to Communicate to Solve Riddles with Deep Distributed Recurrent Q-Networks (2016, background): “There has been a plethora of work on multi-agent reinforcement learning with communication, e.g., (Tan, 1993; Melo et al., 2011; Panait & Luke, 2005; Zhang & Lesser, 2013; Maravall et al., 2013).”