This paper describes the techniques used to build a virtual player for the popular TV game "Who Wants to Be a Millionaire?". The player must answer a series of multiple-choice questions posed in natural language by selecting the correct answer among four different choices. The architecture of the virtual player consists of 1) a Question Answering (QA) module, which leverages Wikipedia and DBpedia datasources to retrieve the most relevant passages of text useful to identify the correct answer to a question, 2) an Answer Scoring (AS) module, which assigns a score to each candidate answer according to different criteria based on the passages of text retrieved by the Question Answering module, and 3) a Decision Making (DM) module, which chooses the strategy for playing the game according to specific rules as wellas to the scores assigned to the candidate answers.We have evaluated both the accuracy of the virtual player to correctly answer to questions of the game, and its ability to play real games in order to earn money. The experiments have been carried out on questions comingfrom the official Italian and English boardgames. The average accuracy of the virtual player for Italian is 79.64%, which is significantly better than the performance of human players, which is equal to 51.33%. The average accuracy of the virtual player for English is 76.41%. The comparison with human players is not carried out for English since, playing successfully the game heavily depends on the players' knowledge about popular culture, and in this experiment we have only involved a sample of Italian players. As regards the ability to play real games, which involves the definition of a proper strategy for the usage of lifelines in order to decide whether to answer to a question even in a condition of uncertainty or to retire from the game by taking the earned money, the virtual player earns € 114,531 on average for Italian, and E 88,878 for English, which exceeds the average amount earned by the human players to a greater extent (€ 5,926 for Italian).

Playing with Knowledge: A Virtual Player for "Who Wants to Be a Millionaire?" that Leverages Question Answering Techniques

LOPS, PASQUALE;SEMERARO, Giovanni;DEGEMMIS, MARCO;BASILE, PIERPAOLO
2015

Abstract

This paper describes the techniques used to build a virtual player for the popular TV game "Who Wants to Be a Millionaire?". The player must answer a series of multiple-choice questions posed in natural language by selecting the correct answer among four different choices. The architecture of the virtual player consists of 1) a Question Answering (QA) module, which leverages Wikipedia and DBpedia datasources to retrieve the most relevant passages of text useful to identify the correct answer to a question, 2) an Answer Scoring (AS) module, which assigns a score to each candidate answer according to different criteria based on the passages of text retrieved by the Question Answering module, and 3) a Decision Making (DM) module, which chooses the strategy for playing the game according to specific rules as wellas to the scores assigned to the candidate answers.We have evaluated both the accuracy of the virtual player to correctly answer to questions of the game, and its ability to play real games in order to earn money. The experiments have been carried out on questions comingfrom the official Italian and English boardgames. The average accuracy of the virtual player for Italian is 79.64%, which is significantly better than the performance of human players, which is equal to 51.33%. The average accuracy of the virtual player for English is 76.41%. The comparison with human players is not carried out for English since, playing successfully the game heavily depends on the players' knowledge about popular culture, and in this experiment we have only involved a sample of Italian players. As regards the ability to play real games, which involves the definition of a proper strategy for the usage of lifelines in order to decide whether to answer to a question even in a condition of uncertainty or to retire from the game by taking the earned money, the virtual player earns € 114,531 on average for Italian, and E 88,878 for English, which exceeds the average amount earned by the human players to a greater extent (€ 5,926 for Italian).
File in questo prodotto:
File Dimensione Formato  
ARTINT-D-13-00329R3.pdf

non disponibili

Tipologia: Documento in Pre-print
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 2.11 MB
Formato Adobe PDF
2.11 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
Playing with knowledge.pdf

non disponibili

Tipologia: Documento in Versione Editoriale
Licenza: NON PUBBLICO - Accesso privato/ristretto
Dimensione 3.31 MB
Formato Adobe PDF
3.31 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11586/103844
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 11
  • ???jsp.display-item.citation.isi??? 7
social impact