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» Learning the required number of agents for complex tasks
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WSC
2004
15 years 1 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»
14 years 10 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
15 years 2 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
15 years 6 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
15 years 1 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