pyCreeper
The main purpose of pyCreeper is to wrap tens of lines of python code, required to produce graphs that look good for a publication, into functions. It takes away your need to understand various quirks of matplotlib and gives you back ready-to-use and well-documented code.
Novelty detection with robots using the Grow-When-Required Neural Network
The Grow-When-Required Neural Network implementation in simulated robot experiments using the ARGoS robot simulator.
Fast Data Analysis Using C++ and Python
C++ code that processes data and makes it available to Python, significantly improving the execution speed.
Designing Robot Swarms
This project looks at the challenges involved in modeling, understanding and designing of multi-robot systems.
Robustness in Foraging E-puck Swarms Through Recruitment
Swarms of five e-puck robots are used in a semi-virtual environment, facilitated by the VICON positioning system. Recruitment can make swarms more robust to noise in robot global positioning data.
The Grow-When-Required Neural Network implementation in simulated robot experiments using the ARGoS...
An ARGoS simulation of robot swarm foraging using various robot controllers and environments. This...
Stigmergy allows insect colonies to collectively build structures that no single individual is...
The original boid flocking algorithm is extended by adding randomised movement to the flock...
Attributes of ultrastability as an adaption mechanism in a hormone-modulated neural robot...
The paper investigates artificial evolution of cooperation in the Iterated Prisoner's Dilemma using...
