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AAMAS
2005
Springer
15 years 2 months ago
Cooperative Multi-Agent Learning: The State of the Art
Cooperative multi-agent systems are ones in which several agents attempt, through their interaction, to jointly solve tasks or to maximize utility. Due to the interactions among t...
Liviu Panait, Sean Luke
ATAL
2009
Springer
15 years 9 months ago
An empirical analysis of value function-based and policy search reinforcement learning
In several agent-oriented scenarios in the real world, an autonomous agent that is situated in an unknown environment must learn through a process of trial and error to take actio...
Shivaram Kalyanakrishnan, Peter Stone
ICML
1999
IEEE
15 years 6 months ago
Learning Hierarchical Performance Knowledge by Observation
Developing automated agents that intelligently perform complex real world tasks is time consuming and expensive. The most expensive part of developing these intelligent task perfo...
Michael van Lent, John E. Laird
135
Voted
SIGMOD
2012
ACM
232views Database» more  SIGMOD 2012»
13 years 5 months ago
Large-scale machine learning at twitter
The success of data-driven solutions to difficult problems, along with the dropping costs of storing and processing massive amounts of data, has led to growing interest in largesc...
Jimmy Lin, Alek Kolcz
151
Voted
AAMAS
2011
Springer
14 years 9 months ago
Using focal point learning to improve human-machine tacit coordination
We consider an automated agent that needs to coordinate with a human partner when communication between them is not possible or is undesirable (tacit coordination games). Specifi...
Inon Zuckerman, Sarit Kraus, Jeffrey S. Rosenschei...