Limited spaces
نویسندگان
چکیده
منابع مشابه
Scheduling Flow - Shops with Limited Buffer Spaces
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Reinforcement learning (RL) has recently gained a lot of popularity partially due to the success of deep Q-learning (DQN) on the Atari suite and AlphaGo. In these online domains DQN-RL performs favorably thanks to its ability to continuously learn at super human speeds. Unfortunately, in many real world applications, such as in robotics, the learning rate is limited due to the speed at which th...
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Existing work on automated negotiations has mainly focused on bilateral negotiations with linear utility functions. It is often assumed that all possible agreements and their utility values are given beforehand. Most real-world negotiations however are much more complex. We introduce a new family of negotiation algorithms that is applicable to domains with many agents, an intractably large spac...
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Existing work on automated negotiations has mainly focused on bilateral negotiations with linear utility functions. It is often assumed that all possible agreements and their utility values are given beforehand. Most real-world negotiations however are much more complex. We introduce a new family of negotiation algorithms that is applicable to domains with many agents, an intractably large spac...
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Methods for planning in multiagent settings often model other agents’ possible behaviors. However, the space of these models – whether these are policy trees, finite-state controllers or intentional models – is very large and thus arbitrarily bounded. This may exclude the true model or the optimal model. In this paper, we present a novel iterative algorithm for online planning that considers a ...
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ژورنال
عنوان ژورنال: Annales mathématiques Blaise Pascal
سال: 1995
ISSN: 1259-1734
DOI: 10.5802/ambp.24