We present the Genetic L-System Programming (GLP) paradigm for evolutionary creation and development of parallel rewrite systems (Lsystems, Lindenmayer-systems) which provide a com...
Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a goal from interactions with the environment. Using Artificial Life techniques we derive ...
Yael Niv, Daphna Joel, Isaac Meilijson, Eytan Rupp...
Background: This work explores the quantitative characteristics of the local transcriptional regulatory network based on the availability of time dependent gene expression data se...
Abstract. In many biological examples of biased random walks, movement statistics are determined by state dynamics that are internal to the organism or cell and that mediate respon...
Spiking neural networks are computationally more powerful than conventional artificial neural networks. Although this fact should make them especially desirable for use in evoluti...
Rich Drewes, James B. Maciokas, Sushil J. Louis, P...