16/01/2019 1:22am
A #neural #network can learn to organize the world it sees into concepts [LINK]
14/01/2019 6:46pm
RT @icouzin: Deadline tomorrow for applications for PhD and Postdoc positions in the “Center for the Advanced Study of Collective Behaviour…
14/01/2019 6:46pm
RT @farscopecdt: We are now accepting applications for PhDs at @BristolRobotLab starting September 2019. See [LINK] for…
11/01/2019 2:19pm
RT @BristolRobotLab: Congratulations!! 🎉🍾 Our old friends @OpenBionics have successfully raised £4.6m from investors incl. F1 team William…
09/01/2019 1:12pm
RT @nekonaute: We are looking for a R&D #engineer in #electronics to design a new robotic platform for #swarmrobotics in #Paris - intereste…

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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.