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.

Towards Smart Robots: Rock-Paper-Scissors Gaming versus Human Players

MICHIELETTO, STEFANO;MENEGATTI, EMANUELE
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.
2013
Electronic
Inglese
Popularize Artificial Intelligence
Matteo Baldoni Federico Chesani Paola Mello Marco Montali
CEUR WORKSHOP PROCEEDINGS
1107
89
95
7
Esperti anonimi
Popularize Artificial Intelligence
Dece,ber 5, 2013
Turin (Italy)
Nazionale
contributo
2-s2.0-84908689764
The AI, Robotics & Automatic Control category is concerned with resources on the research and techniques of artificial intelligence; that is, the creation of machines that exhibit characteristics of human intelligence (e.g., efficient representation of knowledge, reasoning, deduction, problem solving, heuristics, and analysis of contradictory or ambiguous information). Related AI technologies include expert systems, fuzzy systems, natural language processing, speech and pattern recognition, computer vision, decision-support systems, knowledge-bases, and neural networks. Robotics resources are concerned with the design, construction, and operation of robots. Automatic Control resources cover the design and development of regulating processes and systems that replace the necessity of human intervention. Topics include adaptive control, robust control, discrete-event control, dynamic control, fuzzy control, and optimal control. Cybernetics resources are concerned with the control and communication within and between artificial (machine) systems and living or natural systems.
Computer Science & Engineering includes resources on computer hardware and architecture, computer software, software engineering and design, computer graphics, programming languages, theoretical computing, computing methodologies, broad computing topics, and interdisciplinary computer applications.
Gaussian Mixture Model; Machine Learning; human robot interaction; LEGO Mindstorms NXT; Artificial intelligence
http://ceur-ws.org/Vol-1107/paper11.pdf
ITALIA
273
Gabriele, Pozzato; Michieletto, Stefano; Menegatti, Emanuele
3
open
info:eu-repo/semantics/conferenceObject
04 CONTRIBUTO IN ATTO DI CONVEGNO::04.01 - Contributo in atti di convegno
04.01 - Contributo in atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2717681
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