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» Learning to Learn Causal Models
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IPPS
2006
IEEE
15 years 5 months ago
Parallelization of module network structure learning and performance tuning on SMP
As an extension of Bayesian network, module network is an appropriate model for inferring causal network of a mass of variables from insufficient evidences. However learning such ...
Hongshan Jiang, Chunrong Lai, Wenguang Chen, Yuron...
CE
2006
161views more  CE 2006»
14 years 11 months ago
Applying an authentic, dynamic learning environment in real world business
This paper describes a dynamic computer-based business learning environment and the results from applying it in a real-world business organization. We argue for using learning too...
Timo Lainema, Sami Nurmi
MICAI
2005
Springer
15 years 5 months ago
Knowledge and Reasoning Supported by Cognitive Maps
A powerful and useful approach for modeling knowledge and qualitative reasoning is the Cognitive Map. The background of Cognitive Maps is the research about learning environments c...
Alejandro Peña Ayala, Humberto Sossa, Agust...
ICVS
1999
Springer
15 years 4 months ago
Action Reaction Learning: Automatic Visual Analysis and Synthesis of Interactive Behaviour
We propose Action-Reaction Learning as an approach for analyzing and synthesizing human behaviour. This paradigm uncovers causal mappings between past and future events or between...
Tony Jebara, Alex Pentland
ATAL
2008
Springer
15 years 1 months ago
Learning to interact: connecting perception with action in virtual environments
Modeling synthetic characters which interact with objects in dynamic virtual worlds is important when we want the agents to act in an autonomous and non-preplanned way. Such inter...
Pedro Sequeira, Ana Paiva