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» Learning the required number of agents for complex tasks
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AAAI
2008
13 years 10 months ago
Active Learning for Pipeline Models
For many machine learning solutions to complex applications, there are significant performance advantages to decomposing the overall task into several simpler sequential stages, c...
Dan Roth, Kevin Small
ATAL
2004
Springer
14 years 1 months ago
On the Communication Complexity of Multilateral Trading
We study the complexity of a multilateral negotiation framework where autonomous agents agree on a sequence of deals to exchange sets of discrete resources in order to both furthe...
Ulrich Endriss, Nicolas Maudet
JIRS
2000
133views more  JIRS 2000»
13 years 7 months ago
Managing Complexity in Large Learning Robotic Systems
Abstract. Autonomous learning systems of significant complexity often consist of several interacting modules or agents. These modules collaborate to produce a system which, when vi...
Kynan Eng, Alec P. Robertson, Deane R. Blackman
GECCO
2007
Springer
217views Optimization» more  GECCO 2007»
13 years 9 months ago
A quantitative analysis of memory requirement and generalization performance for robotic tasks
In autonomous agent systems, memory is an important element to handle agent behaviors appropriately. We present the analysis of memory requirements for robotic tasks including wal...
DaeEun Kim
AAAI
2007
13 years 10 months ago
Continuous State POMDPs for Object Manipulation Tasks
My research focus is on using continuous state partially observable Markov decision processes (POMDPs) to perform object manipulation tasks using a robotic arm. During object mani...
Emma Brunskill