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SARA
2005
Springer
15 years 11 months ago
Feature-Discovering Approximate Value Iteration Methods
Sets of features in Markov decision processes can play a critical role ximately representing value and in abstracting the state space. Selection of features is crucial to the succe...
Jia-Hong Wu, Robert Givan
GECCO
2009
Springer
121views Optimization» more  GECCO 2009»
15 years 10 months ago
Using memetic algorithms to improve portfolio performance in static and dynamic trading scenarios
The Portfolio Optimization problem consists of the selection of a group of assets to a long-term fund in order to minimize the risk and maximize the return of the investment. This...
Claus de Castro Aranha, Hitoshi Iba
AI
2005
Springer
15 years 6 months ago
Towards a practical theory of reformulation for reasoning about physical systems
In this paper, we propose a practical framework for characterizing, evaluating and selecting reformulation techniques for reasoning about physical systems, with the long-term goal...
Berthe Y. Choueiry, Yumi Iwasaki, Sheila A. McIlra...
TMC
2008
136views more  TMC 2008»
15 years 6 months ago
Efficient Resource Allocation for Wireless Multicast
In this paper, we propose a bandwidth-efficient multicast mechanism for heterogeneous wireless networks. We reduce the bandwidth cost of an Internet Protocol (IP) multicast tree by...
De-Nian Yang, Ming-Syan Chen
IJAR
2010
130views more  IJAR 2010»
15 years 4 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki