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» Learning Abstraction Hierarchies for Problem Solving
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AAAI
2007
13 years 11 months ago
Measuring the Level of Transfer Learning by an AP Physics Problem-Solver
Transfer learning is the ability of an agent to apply knowledge learned in previous tasks to new problems or domains. We approach this problem by focusing on model formulation, i....
Matthew Klenk, Kenneth D. Forbus
ICML
1998
IEEE
14 years 9 months ago
RL-TOPS: An Architecture for Modularity and Re-Use in Reinforcement Learning
This paper introduces the RL-TOPs architecture for robot learning, a hybrid system combining teleo-reactive planning and reinforcement learning techniques. The aim of this system ...
Malcolm R. K. Ryan, Mark D. Pendrith
GECCO
2004
Springer
106views Optimization» more  GECCO 2004»
14 years 2 months ago
Run Transferable Libraries - Learning Functional Bias in Problem Domains
Abstract. This paper introduces the notion of Run Transferable Libraries, a mechanism to pass knowledge acquired in one GP run to another. We demonstrate that a system using these ...
Maarten Keijzer, Conor Ryan, Mike Cattolico
LPAR
2010
Springer
13 years 7 months ago
Partitioning SAT Instances for Distributed Solving
Abstract. In this paper we study the problem of solving hard propositional satisfiability problem (SAT) instances in a computing grid or cloud, where run times and communication b...
Antti Eero Johannes Hyvärinen, Tommi A. Juntt...
GRID
2010
Springer
13 years 6 months ago
Parallel SAT Solving on Peer-to-Peer Desktop Grids
Abstract Satciety is a distributed parallel satisfiability (SAT) solver which focuses on tackling the domainspecific problems inherent to one of the most challenging environments f...
Sven Schulz, Wolfgang Blochinger