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AAMAS
2005
Springer
14 years 11 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
CORR
2011
Springer
178views Education» more  CORR 2011»
14 years 3 months ago
Online Learning: Stochastic and Constrained Adversaries
Learning theory has largely focused on two main learning scenarios. The first is the classical statistical setting where instances are drawn i.i.d. from a fixed distribution and...
Alexander Rakhlin, Karthik Sridharan, Ambuj Tewari
SELMAS
2004
Springer
15 years 5 months ago
A Software Framework for Automated Negotiation
If agents are to negotiate automatically with one another they must share a negotiation mechanism, specifying what possible actions each party can take at any given time, when nego...
Claudio Bartolini, Chris Preist, Nicholas R. Jenni...
SIGMETRICS
2010
ACM
201views Hardware» more  SIGMETRICS 2010»
15 years 4 months ago
Load balancing via random local search in closed and open systems
In this paper, we analyze the performance of random load resampling and migration strategies in parallel server systems. Clients initially attach to an arbitrary server, but may s...
Ayalvadi Ganesh, Sarah Lilienthal, D. Manjunath, A...
CIKM
2011
Springer
13 years 11 months ago
MTopS: scalable processing of continuous top-k multi-query workloads
A continuous top-k query retrieves the k most preferred objects in a data stream according to a given preference function. These queries are important for a broad spectrum of appl...
Avani Shastri, Di Yang, Elke A. Rundensteiner, Mat...