DNA Starts to Learn Poker

14 years 3 months ago

Download www.cis.udel.edu

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 default to the most conservative course, (3) to probabilistically override the default in some cases, and (4) to learn from payoffs. Two players each use an independent population of strategies that adapt and learn from their experiences in competition.

David Harlan Wood, Hong Bi, Steven Orla Kimbrough,

Real-time Traffic

Bioinformatics | Conservative Course | DNA 2001 | Essential Features | Simplified Version |

claim paper

» Predicting DNAbinding sites of proteins from amino acid sequence

» Learning to play Tetris applying reinforcement learning methods

» Apples and oranges avoiding different priors in Bayesian DNA sequence analysis

» Regularized Least Squares Cancer Classifiers from DNA microarray data

» Unifying generative and discriminative learning principles

» Laboratory Information Management Software for genotyping workflows applications in high t...

» Hidden Markov Model Variants and their Application

» Using Bayesian networks to analyze expression data

Post Info
More Details (n/a)

Added	28 Jul 2010
Updated	28 Jul 2010
Type	Conference
Year	2001
Where	DNA
Authors	David Harlan Wood, Hong Bi, Steven Orla Kimbrough, Dong-Jun Wu, Junghuei Chen

Comments (0)

Sciweavers

DNA Starts to Learn Poker

Bioinformatics | Conservative Course | DNA 2001 | Essential Features | Simplified Version |

Explore & Download

Productivity Tools

Document Tools

Image Tools

Sciweavers