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FLAIRS
2008
13 years 7 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
1989
13 years 6 months ago
Filter Preferential Entailment for the Logic of Action in Almost Continuous Worlds
Mechanical systems, of the kinds which are of interest for qualitative reasoning, are characterized by a set of real-valued parameters, each of which is a piecewise continuous fun...
Erik Sandewall
MICAI
2009
Springer
14 years 1 days ago
A Two-Stage Relational Reinforcement Learning with Continuous Actions for Real Service Robots
Reinforcement Learning is a commonly used technique in robotics, however, traditional algorithms are unable to handle large amounts of data coming from the robot’s sensors, requi...
Julio H. Zaragoza, Eduardo F. Morales
SASO
2007
IEEE
13 years 11 months ago
Continuous Space-Time Semantics Allow Adaptive Program Execution
Jonathan Bachrach, Jacob Beal, Takeshi Fujiwara
HICSS
2005
IEEE
147views Biometrics» more  HICSS 2005»
13 years 11 months ago
Branching Process Models for the Exponentially Increasing Portions of Cascading Failure Blackouts
We introduce branching process models in discrete and continuous time for the exponentially increasing phase of cascading blackouts. Cumulative line trips from real blackout data ...
Ian Dobson, Benjamin A. Carreras, David E. Newman