[Tweets]

18/10/2021 10:24pm
RT @petitegeek: “If we could understand what information the predictive models were using, we could ask for feedback that improved our whol…
16/10/2021 6:43am
This week ends with a finished design for a prototype electric car website. What do you think? Would you buy the ca… [LINK]
05/10/2021 4:14am
RT @vitotrianni: Two PhD positions in collaboration between @cnr_istc and @SapienzaRoma will open soon. The research focuses on #robotics a…
04/10/2021 9:14am
A new office pet has arrived :) [LINK]
01/10/2021 10:46pm
Just published: A new case study about a website that I made for my research project about robot swarms.… [LINK]

[Uwo]

Games Flash ActionScript Date: Jan 2005

Uwo Technologies used: ActionScript 2

Get through three exciting desert levels on a motorbike without crashing. But don't forget to pick up hitchhikers - otherwise you won't be able to progress. Collect a code after each level to be able to return to it.

Run Uwo
Controls: The arrow keys


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Jigsaw

This is a jigsaw puzzle that was used in the game Mayan Madness. The pieces are placed randomly throughout the screen each time a game starts. Developer can insert pieces of a different image and assemble it from the Flash development environment. The algorithm takes care of the rest - random positioning and testing of the end game state.

Bouncy Ball

Jump with the bouncy ball through the platforms and collect golden treasures to get to the next level. This demo offers three levels to play. At the beginning of each level, you get a code that can be used later in order to skip to the level using the Load game feature.

Ludo

A two-player game based on Ludo where you do not have to roll dice anymore. The goal of both players is to get to the middle of the board. However, there are some evil caterpillars on the way that will not let anybody through.

Pac Man

This demo shows a Pac Man-like game with the Southpark theme. Control Eric Cartman to collect points while avoiding your enemies.

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.