May, 24th, 2023 CREF TALK
Title: Economic Complexity and the Knowledge Diffusion in Europe
Speaker: Daniela Cialfi , University of Teramo
Title: Economic Complexity and the Knowledge Diffusion in Europe
Speaker: Daniela Cialfi , University of Teramo
CREF Talk April, 26th 2023
The quality of specialization and export performance of local economies: methodological issues
Speaker : Lelio Iapadre (University of L’Aquila and UNU-CRIS, Bruges)
Speaker : Lelio Iapadre (University of L’Aquila and UNU-CRIS, Bruges)
Mentre ChatGpt resta sospesa in Italia dal Garante della privacy, che ha chiesto una serie di garanzie al software californiano entro aprile, ogni giorno continua il dibattito sull'uso dell'intelligenza artificiale (...)
Esistono più possibili partite di scacchi che atomi nell’universo osservabile: si stima che il gioco degli scacchi abbia una complessità di circa 10120, ossia uno seguito da centoventi zeri (è il cosiddetto numero di Shannon). O, ancora: dopo che bianco e nero hanno fatto cinque mosse ciascuno, ci sono 69.352.859.712.417 possibili partite che possono essere state sviluppate.
Quantifying the complexity and similarity of chess openings using online chess community data
Giordano De Marzo & Vito D. P. Servedio
Scientific Reports volume 13
Chess is a centuries-old game that continues to be widely played worldwide. Opening Theory is one of the pillars of chess and requires years of study to be mastered. In this paper, we use the games played in an online chess platform to exploit the “wisdom of the crowd” and answer questions traditionally tackled by chess experts. We first define a relatedness network of chess openings that quantifies how similar two openings are to play. Using this network, we identify communities of nodes corresponding to the most common opening choices and their mutual relationships.
Giordano De Marzo & Vito D. P. Servedio
Scientific Reports volume 13
Chess is a centuries-old game that continues to be widely played worldwide. Opening Theory is one of the pillars of chess and requires years of study to be mastered. In this paper, we use the games played in an online chess platform to exploit the “wisdom of the crowd” and answer questions traditionally tackled by chess experts. We first define a relatedness network of chess openings that quantifies how similar two openings are to play. Using this network, we identify communities of nodes corresponding to the most common opening choices and their mutual relationships.
