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FLAIRS
2008
15 years 6 months ago
Learning Continuous Action Models in a Real-Time Strategy Environment
Although several researchers have integrated methods for reinforcement learning (RL) with case-based reasoning (CBR) to model continuous action spaces, existing integrations typic...
Matthew Molineaux, David W. Aha, Philip Moore
IJCAI
2001
15 years 5 months ago
Leveraging Data About Users in General in the Learning of Individual User Models
Models of computer users that are learned on the basis of data can make use of two types of information: data about users in general and data about the current individual user. Fo...
Anthony Jameson, Frank Wittig
ACL
1998
15 years 5 months ago
Maximum Entropy Model Learning of the Translation Rules
This paper proposes a learning method of translation rules from parallel corpora. This method applies the maximum entropy principle to a probabilistic model of translation rules. ...
Kengo Sato, Masakazu Nakanishi
NN
2006
Springer
15 years 4 months ago
Machine learning in sedimentation modelling
The paper presents machine learning (ML) models that predict sedimentation in the harbour basin of the Port of Rotterdam. The important factors affecting the sedimentation process...
Biswanath Bhattacharya, Dimitri P. Solomatine
JAIR
2008
148views more  JAIR 2008»
15 years 4 months ago
Learning Partially Observable Deterministic Action Models
We present exact algorithms for identifying deterministic-actions' effects and preconditions in dynamic partially observable domains. They apply when one does not know the ac...
Eyal Amir, Allen Chang