246 search results - page 35 / 50 » Learning behavior styles with inverse reinforcement learning |
166
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ICCAD
2008
IEEE
16 years 11 days ago
2008
IEEE
This paper presents ISCLEs, a novel and robust analog design method that promises to scale with Moore’s Law, by doing boosting-style importance sampling on digital-sized circuit...
161
Voted
ATAL
2009
Springer
16 years 15 days ago
2009
Springer
In this paper, we study multi-agent economic systems using a recent approach to economic modeling called Agent-based Computational Economics (ACE): the application of the Complex ...
137
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AAAI
2000
15 years 7 months ago
2000
We have constructed ADVISOR, a two-agent machine learning architecture for intelligent tutoring systems (ITS). The purpose of this architecture is to centralize the reasoning of a...
176
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CIA
2007
Springer
16 years 3 days ago
2007
Springer
When two or more agents interacting, their behaviors are not necessarily matching. Automated ways to overcome con icts in the behavior of agents can make the execution of interacti...
164
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SMC
2007
IEEE
16 years 6 days ago
2007
IEEE
—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...