Synthetic biology is the engineering discipline for constructing novel organisms with functions that do not exist in nature. We recently engineered a prototype CMY genetic circuit that visually produces cyan, magenta, and yellow colors independently and in combination using different inducer molecules. Since the production of each color can be independently controlled, this allows for the produ...

It has been hypothesized that the evolution of sensors is a pivotal driver for the evolution of organisms, and especially, as a crucial part of the perception-action loop, a driver for cognitive development. The questions of why and how this is the case are important: what are the principles that push the evolution of sensorimotor systems? An interesting aspect of this problem is the co-option ...

We have developed a theoretical framework for developing patterns in multiple dimensions using controllable diffusion and designed reactions implemented in DNA. This includes socalled strand displacement reactions in which one singlestranded DNA hybridizes to a hemi-duplex DNA and displaces another single stranded DNA, reversibly or irreversibly. These reactions can be designed to proceed with ...

We propose and evaluate a novel approach called Online Distributed NeuroEvolution of Augmenting Topologies (odNEAT). odNEAT is a completely distributed evolutionary algorithm for online learning in groups of embodied agents such as robots. While previous approaches to online distributed evolution of neural controllers have been limited to the optimisation of weights, odNEAT evolves both weights...

Neural Baldwinism concerns the Baldwin Effect in the evolution of brains and intelligence. The first phase of the Baldwin Effect (B.E.), wherein plasticity provides a selective advantage, is intuitive and commonplace in simulations of adaptive systems. However, the second (assimilation) phase often poses problems for Baldwinism in general, and this is particularly acute for biological neural ne...

We introduce replicator-mutator mechanisms from evolutionary dynamics into a two-dimensional daisyworld model, thereby coupling evolutionary changes with daisyworld’s bidirectional feedback between biota and environment. Daisyworld continues to self-regulate in the presence of these evolutionary forces. The most interesting behaviours, exhibiting a complex and dynamic dance through space and ti...

A pair of Continuous-time Recurrent Neural Network (CTRNN) based agents called “Sender” and “Receiver” is evolved on a circular world. Their collective objective is to communicate and move to a target – the Sender needs to communicate the address of a target location on the circle, and the Receiver needs to move to that location after receiving the communication. In extension of previous work (...

Most self-organizing models of moving agent collectives (simulated herds, bird flocks, etc.) employ reflexive agents that lack significant memory of past movements and previously encountered environmental features. Further, these agent collectives often act in fairly open environments where obstacles to movement are relatively sparse. In this work, we explore the hypothesis that a limited worki...

We present a new artificial chemistry simulator based on simple physical and chemical rules. The simulator relies on a simplification of bonding and internal energy concepts found in chemistry to model simple, large scale, chemical reactions without delay between computation and visualization. Energy introduction and removal can be controlled in the simulations in order to modulate reaction rat...