Role-Based Multi-Agent Systems

By Haibin Zhu, Mengchu Zhou. 2008

17 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Information Systems

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. Chongjie Zhang
2. Tonghan Wang
3. Bei Peng
4. Shimon Whiteson
5. Heng Dong
6. Anuj Mahajan
7. Tarun Gupta
8. Victor R. Lesser

In Computer Networks and Communications

1. Tonghan Wang
2. Chongjie Zhang
3. Shimon Whiteson
4. Heng Dong
5. Victor R. Lesser
6. Bei Peng
7. Aadirupa Saha
8. Jianhao Wang

In Information Systems

1. Shimon Whiteson
2. Maarten de Rijke
3. Masrour Zoghi

Citations in the corpus

• RODE: Learning Roles to Decompose Multi-Agent Tasks (2020, background): “…the task and specializing agents with the same role to certain sub-tasks (Wooldridge et al., 2000; Omicini, 2000; Padgham & Winikoff, 2002; Pav´on & G´omez-Sanz, 2003; Cossentino et al., 2005; Zhu & Zhou, 2008; Spanoudakis & Moraitis, 2010; DeLoach & Garcia-Ojeda, 2010; Bonjean et al., 2014).”
• ROMA: Multi-Agent Reinforcement Learning with Emergent Roles (2020, background): “In these role-based frameworks, the complexity of agent design is reduced via task decomposition by defining roles which are associated with respon-sibilities made up of a set of sub-tasks, so that the policy search space is effectively decomposed (Zhu & Zhou, 2008).”