Towards Smart Robots: Rock-Paper-Scissors Gaming versus Human Players
Contributo in Atti di convegno
Data di Pubblicazione:
2013
Abstract:
In this project a human robot interaction system was developed
in order to let people naturally play rock-paper-scissors games
against a smart robotic opponent. The robot does not perform random
choices, the system is able to analyze the previous rounds trying to forecast
the next move. A Machine Learning algorithm based on Gaussian
Mixture Model (GMM) allows us to increase the percentage of robot victories.
This is a very important aspect in the natural interaction between
human and robot, in fact, people do not like playing against “stupid”
machines, while they are stimulated in confronting with a skilled opponent.
in order to let people naturally play rock-paper-scissors games
against a smart robotic opponent. The robot does not perform random
choices, the system is able to analyze the previous rounds trying to forecast
the next move. A Machine Learning algorithm based on Gaussian
Mixture Model (GMM) allows us to increase the percentage of robot victories.
This is a very important aspect in the natural interaction between
human and robot, in fact, people do not like playing against “stupid”
machines, while they are stimulated in confronting with a skilled opponent.
Tipologia CRIS:
04.01 - Contributo in atti di convegno
Keywords:
Gaussian Mixture Model; Machine Learning; human robot interaction; LEGO Mindstorms NXT; Artificial intelligence
Elenco autori:
Gabriele, Pozzato; Michieletto, Stefano; Menegatti, Emanuele
Link alla scheda completa:
Link al Full Text:
Titolo del libro:
Popularize Artificial Intelligence
Pubblicato in: