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PKDD
2009
Springer
102views Data Mining» more  PKDD 2009»
15 years 6 months ago
Relevance Grounding for Planning in Relational Domains
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
Tobias Lang, Marc Toussaint
ECTEL
2007
Springer
15 years 6 months ago
CAMEL: Taking the Technology Enhanced Learning Journey without Reinventing the Wheel
Projects involving technology are notoriously dogged with difficulties and a number of lessons can be learned. Rather than detail examples from particular TEL projects, the author ...
Gill Ferrell
ICASSP
2011
IEEE
14 years 3 months ago
Bayesian reinforcement learning for POMDP-based dialogue systems
Spoken dialogue systems are gaining popularity with improvements in speech recognition technologies. Dialogue systems can be modeled effectively using POMDPs, achieving improvemen...
ShaoWei Png, Joelle Pineau
NIPS
1993
15 years 1 months ago
The Parti-Game Algorithm for Variable Resolution Reinforcement Learning in Multidimensional State-Spaces
Parti-game is a new algorithm for learning feasible trajectories to goal regions in high dimensionalcontinuousstate-spaces. In high dimensions it is essential that learningdoes not...
Andrew W. Moore
CE
2005
84views more  CE 2005»
14 years 11 months ago
Virtual collaborative learning environments for music: networked drumsteps
This paper focuses on technologies that enable meaningful, constructionist interaction in collaborative music environments. In particular, it describes the design and implementati...
Conor McCarthy, James Bligh, Kevin Jennings, Brend...