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» Learning the required number of agents for complex tasks
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WSC
2004
13 years 9 months ago
A Generalized Multiple Response Surface Methodology for Complex Computer Simulation Applications
This work provides a generalization of the traditional response surface methodology (RSM) that can be applied to complex, multi-objective simulation studies. These problems involv...
Jeffrey B. Schamburg, Donald E. Brown
ICRA
2010
IEEE
133views Robotics» more  ICRA 2010»
13 years 6 months ago
Generalized model learning for Reinforcement Learning on a humanoid robot
— Reinforcement learning (RL) algorithms have long been promising methods for enabling an autonomous robot to improve its behavior on sequential decision-making tasks. The obviou...
Todd Hester, Michael Quinlan, Peter Stone
AAAI
2007
13 years 10 months ago
Learning by Reading: A Prototype System, Performance Baseline and Lessons Learned
A traditional goal of Artificial Intelligence research has been a system that can read unrestricted natural language texts on a given topic, build a model of that topic and reason...
Ken Barker, Bhalchandra Agashe, Shaw Yi Chaw, Jame...
IAT
2008
IEEE
14 years 2 months ago
An Ontology-Driven Framework for Deploying JADE Agent Systems
Multi-agent systems have proven to be a powerful technology for building complex distributed applications. However, the process of designing, configuring and deploying agent-based...
Csongor Nyulas, Martin J. O'Connor, Samson W. Tu, ...
AAAI
2010
13 years 9 months ago
Compilation Complexity of Common Voting Rules
In computational social choice, one important problem is to take the votes of a subelectorate (subset of the voters), and summarize them using a small number of bits. This needs t...
Lirong Xia, Vincent Conitzer