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ICML
2001
IEEE
15 years 11 months ago
Continuous-Time Hierarchical Reinforcement Learning
Hierarchical reinforcement learning (RL) is a general framework which studies how to exploit the structure of actions and tasks to accelerate policy learning in large domains. Pri...
Mohammad Ghavamzadeh, Sridhar Mahadevan
EDUTAINMENT
2006
Springer
15 years 1 months ago
A Theatre of Ethics and Interaction? Bertolt Brecht and Learning to Behave in First-Person Shooter Environments
This paper explores the nature of player behaviour in game environments in relation to the methodology of the dramatist Bertolt Brecht. Firstly, a conceptualisation of how manipula...
Dan Pinchbeck
ICML
2008
IEEE
15 years 11 months ago
The asymptotics of semi-supervised learning in discriminative probabilistic models
Semi-supervised learning aims at taking advantage of unlabeled data to improve the efficiency of supervised learning procedures. For discriminative models however, this is a chall...
François Yvon, Nataliya Sokolovska, Olivier...
ICALT
2009
IEEE
15 years 4 months ago
ICOPER Big Picture Modelling the Central Concepts of Competency-Driven Learning
Competency based learning is seen as a means to make the educational system more adapt to cater for , the learners’ professional development and the need to increase their futur...
Tore Hoel, Vana Kamtsiou
ICNC
2005
Springer
15 years 3 months ago
Modeling Human Learning as Context Dependent Knowledge Utility Optimization
Abstract. Humans have the ability to flexibly adjust their information processing strategy according to situational characteristics. However, such ability has been largely overloo...
Toshihiko Matsuka