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» Optimization by Stochastic Continuation
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EUROGP
2008
Springer
15 years 8 months ago
PlasmidPL: A Plasmid-Inspired Language for Genetic Programming
We present PlasmidPL, a plasmid-inspired programming language designed for Genetic Programming (GP), and based on a chemical metaphor. The basic data structures in PlasmidPL are ci...
Lidia Yamamoto
149
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AAAI
2006
15 years 8 months ago
When a Decision Tree Learner Has Plenty of Time
The majority of the existing algorithms for learning decision trees are greedy--a tree is induced top-down, making locally optimal decisions at each node. In most cases, however, ...
Saher Esmeir, Shaul Markovitch
155
Voted
NIPS
2001
15 years 8 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...
AAAI
1998
15 years 8 months ago
Solving Very Large Weakly Coupled Markov Decision Processes
We present a technique for computing approximately optimal solutions to stochastic resource allocation problems modeled as Markov decision processes (MDPs). We exploit two key pro...
Nicolas Meuleau, Milos Hauskrecht, Kee-Eung Kim, L...
154
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WSC
1998
15 years 7 months ago
Informational Macrodynamics: System Modelling and Simulation Methodologies
Informational Macrodynamics (IMD) presents a unified informational systemic approach with common information language for modeling, analysis and optimization of a variety of inter...
Vladimir S. Lerner