[Boid Game-Playing through Randomised Movement]

Multi-agent systems Java AI Simulation models Date: Oct 2012

Simulation of boids Technologies used: Java, JFreeChart, Model-View-Controller, Git

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.

DOWNLOAD PAPER DOWNLOAD CODE
RUN JAVA APPLET


{Please enable JavaScript in order to post comments}

Starting my PhD Next Week

I have finally finished making my studio in Southmapton at least decently homey as I am starting my PhD programme on Tuesday. I met some of my classmates yesterday (Saturday) during a barbeque and I am very excited about our future discussions and beer drinking.

Ultrastable Neuroendocrine Robot Controller

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.

Robot Flocking: Sensors and Control

This paper discusses various kinds of robot sensory input, approaches to motor control and ways they could be used for flocking. Focus is put on vision and Gibsonian optic flow that could be utilised by robots with advanced behaviour.

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.