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NIPS
2004
13 years 10 months ago
Convergence and No-Regret in Multiagent Learning
Learning in a multiagent system is a challenging problem due to two key factors. First, if other agents are simultaneously learning then the environment is no longer stationary, t...
Michael H. Bowling
AAAI
2010
13 years 10 months ago
Multi-Agent Learning with Policy Prediction
Due to the non-stationary environment, learning in multi-agent systems is a challenging problem. This paper first introduces a new gradient-based learning algorithm, augmenting th...
Chongjie Zhang, Victor R. Lesser
SIGCOMM
2006
ACM
14 years 2 months ago
In VINI veritas: realistic and controlled network experimentation
This paper describes VINI, a virtual network infrastructure that allows network researchers to evaluate their protocols and services in a realistic environment that also provides ...
Andy C. Bavier, Nick Feamster, Mark Huang, Larry L...
ICAC
2009
IEEE
14 years 3 months ago
vManage: loosely coupled platform and virtualization management in data centers
: © vManage: Loosely Coupled Platform and Virtualization Management in Data Centers Sanjay Kumar, Vanish Talwar, Vibhore Kumar, Parthasarathy Ranganathan, Karsten Schwan HP Labora...
Sanjay Kumar, Vanish Talwar, Vibhore Kumar, Partha...
ATAL
2006
Springer
14 years 18 days ago
Learning empathy: a data-driven framework for modeling empathetic companion agents
Affective reasoning plays an increasingly important role in cognitive accounts of social interaction. Humans continuously assess one another's situational context, modify the...
Scott W. McQuiggan, James C. Lester