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,...
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...
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...
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...
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