[Tweets]

09/08/2022 2:00am
A digital twin for #autonomous #uavs - using the tool we developed, we can simulate a UAV #swarm and even control… [LINK]
11/05/2022 12:24am
Proud to showcase our new #digitaltwin application that enables us to put simulated and real-life #autonomous[LINK]
17/03/2022 4:11am
RT @sabinehauert: Nice to present results of the @evo_nano project along with the whole team. Learn more about the EVONANO platform for the…
21/01/2022 6:27am
"Automated" (#autonomous ?) #drones soon to be at work at the Port of Hamburg. Sounds exciting! [LINK]
04/01/2022 2:04am
An interesting article on state-of-the art in #drone #sensor solutions [LINK]

[Neural Networks and Evolution of Cooperation]

Neural networks Java AI Simulation models Date: Jan 2011

DOWNLOAD PAPER DOWNLOAD CODE RUN JAVA APPLET
Technologies used: Java, JFreeChart, Ant Script, Model-View-Controller, Git

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, described here for the first time.

Evaluation is performed in terms of number of generations needed for reaching a desired cooperation level. The nature of the evolved strategies is also evaluated. Examples when the action-discriminating model evolved the most beneficent strategies are given.

The network schema


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Does Communication Make a Difference?

This paper compares different animal groups from eusocial insect colonies to human society and discusses their mechanics and behaviour as agent systems. The main focus is on interaction between the agents and on how properties of a system like effectiveness or predictability are affected by these interactions.

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.