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» DNA Starts to Learn Poker
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DNA
2001
Springer
14 years 3 months ago
DNA Starts to Learn Poker
DNA is used to implement a simplified version of poker. Strategies are evolved that mix bluffing with telling the truth. The essential features are (1) to wait your turn, (2) to de...
David Harlan Wood, Hong Bi, Steven Orla Kimbrough,...
AAAI
2008
14 years 1 months ago
Bayes-Relational Learning of Opponent Models from Incomplete Information in No-Limit Poker
We propose an opponent modeling approach for no-limit Texas hold-em poker that starts from a (learned) prior, i.e., general expectations about opponent behavior and learns a relat...
Marc J. V. Ponsen, Jan Ramon, Tom Croonenborghs, K...
BMCBI
2006
95views more  BMCBI 2006»
13 years 11 months ago
Predicting DNA-binding sites of proteins from amino acid sequence
Background: Understanding the molecular details of protein-DNA interactions is critical for deciphering the mechanisms of gene regulation. We present a machine learning approach f...
Changhui Yan, Michael Terribilini, Feihong Wu, Rob...
ESANN
2008
14 years 7 days ago
Learning to play Tetris applying reinforcement learning methods
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
Alexander Groß, Jan Friedland, Friedhelm Sch...
BMCBI
2010
152views more  BMCBI 2010»
13 years 11 months ago
Apples and oranges: avoiding different priors in Bayesian DNA sequence analysis
Background: One of the challenges of bioinformatics remains the recognition of short signal sequences in genomic DNA such as donor or acceptor splice sites, splicing enhancers or ...
Jens Keilwagen, Jan Grau, Stefan Posch, Ivo Grosse