Learning to Coordinate Actions in Multi-Agent-Systems

By Gerhard Weiss. 1993

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Citations in the corpus

Multiagent Learning: Basics, Challenges, and Prospects (2012, background): “…which this classification was derived are Haynes, Lau, and Sen (1996); Vidal and Durfee (1996) (multiplied learning), Sen, Sekaran, and Hale (1994) and Weiss (1993) (divided learning), and Bui, Kieronska, and Venkatesh (1996) and Nagendra Prasad, Lesser, and Lander (1996) (interactive learning).”
Hierarchical Chunking in Classifier Systems (2008, methodology): “The criteria used for triggering formation and dissolution are conceptually similar to (and, in fact, have been inspired by) the group-development criteria proposed by Weiß (1993a, 1993b ) in the context of BBA-based multi-agent learning.”
The Dynamics of Reinforcement Learning in Cooperative Multiagent Systems (1998, methodology): “Application of Q-learning and other RL methods have met with some success in the past [22, 16, 17, 15].”
Learning Conventions in Multiagent Stochastic Domains using Likelihood Estimates (1996, background): “task allocation [18, 17] or simply inform one another what actions they will choose.”
Reaching pareto-optimality in prisoner’s dilemma using conditional joint action learning (2007, background): “Introduction The problem of learning in multi agent system has attracted increasing attention in the recent past (Wellman & Hu 1998; Hu & Wellman 2003; Littman 1994; Claus & Boutilier 1997; Littman 2001; Matsubara, Noda, & Hiraki 1996; Bowling & Veloso 2004; Littman & Stone 2001).”
Reinforcement learning of coordination in cooperative multi-agent systems (2002, background): “Learning to coordinate in cooperative multi-agent systems is a central and widely studied problem, see, for example (Lauer & Riedmiller 2000), (Boutilier 1999), (Claus & Boutilier 1998), (Sen & Sekaran 1998), (Sen, Sekaran, & Hale 1994), ( Weiss 1993 ).”
Planning, Learning and Coordination in Multiagent Decision Processes (1996, background): “For example, agents might communicate in order to determine task allocation [37, 57]; conventions (or social laws) might be imposed by the system designed so that optimal joint action is assured [31, 48]; or a coordinated policy (or conventions) might be learned through repeated interaction [47, 46,”
Sequential Optimality and Coordination in Multiagent Systems (1999, background): “…(a) the design of conventions or social laws that restrict agents to selecting coordinated actions [9, 15]; (b) allowing communication among agents before action selection [16]; and (c) the use of learning methods, whereby agents learn to coordinate through repeated interaction [5, 6, 8, 11].”