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» Modeling task allocation using a decision theoretic model
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CP
2007
Springer
15 years 5 months ago
Scheduling Conditional Task Graphs
The increasing levels of system integration in Multi-Processor System-on-Chips (MPSoCs) emphasize the need for new design flows for efficient mapping of multi-task applications o...
Michele Lombardi, Michela Milano
SSPR
2010
Springer
14 years 10 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...
ICML
2006
IEEE
16 years 15 days ago
Using inaccurate models in reinforcement learning
In the model-based policy search approach to reinforcement learning (RL), policies are found using a model (or "simulator") of the Markov decision process. However, for ...
Pieter Abbeel, Morgan Quigley, Andrew Y. Ng
TSMC
1998
132views more  TSMC 1998»
14 years 11 months ago
Decision support for vehicle dispatching using genetic programming
—Vehicle dispatching consists of allocating real-time service requests to a fleet of moving vehicles. In this paper, each vehicle is associated with a vector of attribute values...
Ilham Benyahia, Jean-Yves Potvin
AIPS
2006
15 years 1 months ago
Combining Stochastic Task Models with Reinforcement Learning for Dynamic Scheduling
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
Malcolm J. A. Strens