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ILP
2003
Springer
14 years 28 days ago
Graph Kernels and Gaussian Processes for Relational Reinforcement Learning
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...
Thomas Gärtner, Kurt Driessens, Jan Ramon
IROS
2009
IEEE
146views Robotics» more  IROS 2009»
14 years 2 months ago
Robust constraint-consistent learning
— Many everyday human skills can be framed in terms of performing some task subject to constraints imposed by the environment. Constraints are usually unobservable and frequently...
Matthew Howard, Stefan Klanke, Michael Gienger, Ch...
ILP
2007
Springer
14 years 1 months ago
Learning to Assign Degrees of Belief in Relational Domains
A recurrent question in the design of intelligent agents is how to assign degrees of beliefs, or subjective probabilities, to various events in a relational environment. In the sta...
Frédéric Koriche
AI
1999
Springer
13 years 7 months ago
RoboCup: Today and Tomorrow - What we have learned
RoboCup is an increasingly successful attempt to promote the full integration of AI and robotics research. The most prominent feature of RoboCup is that it provides the researcher...
Minoru Asada, Hiroaki Kitano, Itsuki Noda, Manuela...
ICALT
2003
IEEE
14 years 1 months ago
Educational Robotics in a Systems Design Masters Program
This paper presents the concepts of our MoRob (Modular Educational Robotic Toolbox) project, which aims to provide a robot platform for university teaching and research. Character...
Uwe Gerecke, Patrick Hohmann, Bernardo Wagner