Sciweavers

88 search results - page 10 / 18
» Learning to Coordinate Actions in Multi-Agent-Systems
Sort
View
NIPS
2003
13 years 8 months ago
Learning Near-Pareto-Optimal Conventions in Polynomial Time
We study how to learn to play a Pareto-optimal strict Nash equilibrium when there exist multiple equilibria and agents may have different preferences among the equilibria. We focu...
Xiao Feng Wang, Tuomas Sandholm
HICSS
2009
IEEE
94views Biometrics» more  HICSS 2009»
14 years 2 months ago
Enhancing Learning Experiences in Partially Distributed Teams: Training Students to Work Effectively Across Distances
Three training modules were designed to decrease ingroup dynamics in Partially Distributed Teams, which have two or more geographically separated subteams. The action research ori...
Rosalie J. Ocker, Dana Kracaw, Starr Roxanne Hiltz...
IROS
2007
IEEE
132views Robotics» more  IROS 2007»
14 years 1 months ago
Hysteretic q-learning : an algorithm for decentralized reinforcement learning in cooperative multi-agent teams
— Multi-agent systems (MAS) are a field of study of growing interest in a variety of domains such as robotics or distributed controls. The article focuses on decentralized reinf...
Laëtitia Matignon, Guillaume J. Laurent, Nadi...
AGENTS
2001
Springer
14 years 1 hour ago
Hierarchical multi-agent reinforcement learning
In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multi-agent tasks. We introduce a hierarchical multi-a...
Rajbala Makar, Sridhar Mahadevan, Mohammad Ghavamz...
CMOT
1999
143views more  CMOT 1999»
13 years 7 months ago
Structural Learning: Attraction and Conformity in Task-Oriented Groups
This study extends previous research that showed how informal social sanctions can backfire when members prefer friendship over enforcement of group norms. We use a type of neural...
James A. Kitts, Michael W. Macy, Andreas Flache