[Tweets]

10/12/2018 7:08pm
RT @karpathy: Incredible NeurIPS talk from @drmichaellevin on "Bioelectric Computation Outside the Nervous System" [LINK]
06/12/2018 6:39pm
We are looking for 2x part-time Java developers to work on an awesome editor for a multi-agent systems modelling la… [LINK]
06/12/2018 5:12pm
Excited to announce that we have been awarded the @EPSRC Impact Accelerator Kickstarter Award in collaboration with… [LINK]
03/12/2018 8:39pm
RT @BristolRobotLab: Cafe opens in Tokyo staffed by robots controlled by paralyzed people [LINK] via @RocketNews24En

[Search by tag: Simulation models]

Novelty detection with robots using the Grow-When-Required Neural Network

Simulation models C++ Bash script Date: 12/09/2018 :: 0 comments

The Grow-When-Required Neural Network implementation in simulated robot experiments using the ARGoS robot simulator.

A Highly Customisable Multi-Robot Foraging Simulation

Simulation models C++ Bash script Date: 20/02/2017 :: 0 comments

An ARGoS simulation of robot swarm foraging using various robot controllers and environments. This code has been used in various papers (see References) and thus allows to run different types of simulations.

Controlling Ant-Based Construction

Multi-agent systems Java Simulation models Date: 02/04/2013 :: 0 comments

Stigmergy allows insect colonies to collectively build structures that no single individual is fully aware of. Since relatively minimal sensory and reasoning capabilities are required of the agents, such building activity could be utilised by robotic swarms if we could learn how to control the shape of the final structures.

Boid Game-Playing through Randomised Movement

Multi-agent systems Java AI Simulation models Date: 22/10/2012 :: 0 comments

The original boid flocking algorithm is extended by adding randomised movement to the flock members. This approach is a light-weight alternative to other ‘follow the leader’ techniques implemented in order to create a ‘game-playing’ behaviour during which a flock changes its movement direction as observed in real birds.

Ultrastable Neuroendocrine Robot Controller

Neural networks Java AI Simulation models Date: 15/08/2011 :: 0 comments

Attributes of ultrastability as an adaption mechanism in a hormone-modulated neural robot controller were investigated in a simulation. Action-selection based on hormone-driven utilities of memory items was used to alternate between mineral gathering and recharging.

Neural Networks and the Evolution of Cooperation

Neural networks Java AI Simulation models Date: 16/01/2011 :: 0 comments

The paper investigates artificial evolution of cooperation in the Iterated Prisoner's Dilemma using a number of player implementations. Existing strategy encoding and neural network models are compared with action-discriminating neural network created during writing of this paper.

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.