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Inferring Personality Types for Better Automated Negotiation

Automated negotiation between computational agents or between agents and humans has been a subject of active research with a focus on obtaining better quality solutions within reasonable time frames. The critical issue negotiators face during automated negotiation is that a negotiator may not always...

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Autores principales: Pucha, Sai Naveen, Paruchuri, Praveen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215177/
http://dx.doi.org/10.1007/978-3-030-48641-9_11
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author Pucha, Sai Naveen
Paruchuri, Praveen
author_facet Pucha, Sai Naveen
Paruchuri, Praveen
author_sort Pucha, Sai Naveen
collection PubMed
description Automated negotiation between computational agents or between agents and humans has been a subject of active research with a focus on obtaining better quality solutions within reasonable time frames. The critical issue negotiators face during automated negotiation is that a negotiator may not always know the personality type of the opponent. Studies show that having information about the opponent improves the outcome of negotiation in general. However, unless there is prior knowledge, learning the opponent type in the limited amount of time or number of rounds in a negotiation is a difficult task. In this paper, we use a Partially Observable Markov Decision Process (POMDP) based modeling to perform better modeling of the opponent personality type. In particular, we focus on modeling the opponent into four different types to showcase that a better understanding of personality type can improve the outcome of automated negotiation. Our experiments performed using data sets generated from the IAGO software showcase that we indeed obtain better negotiation outcomes with a higher classification accuracy of the opponent personality type.
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spelling pubmed-72151772020-05-12 Inferring Personality Types for Better Automated Negotiation Pucha, Sai Naveen Paruchuri, Praveen Group Decision and Negotiation: A Multidisciplinary Perspective Article Automated negotiation between computational agents or between agents and humans has been a subject of active research with a focus on obtaining better quality solutions within reasonable time frames. The critical issue negotiators face during automated negotiation is that a negotiator may not always know the personality type of the opponent. Studies show that having information about the opponent improves the outcome of negotiation in general. However, unless there is prior knowledge, learning the opponent type in the limited amount of time or number of rounds in a negotiation is a difficult task. In this paper, we use a Partially Observable Markov Decision Process (POMDP) based modeling to perform better modeling of the opponent personality type. In particular, we focus on modeling the opponent into four different types to showcase that a better understanding of personality type can improve the outcome of automated negotiation. Our experiments performed using data sets generated from the IAGO software showcase that we indeed obtain better negotiation outcomes with a higher classification accuracy of the opponent personality type. 2020-04-25 /pmc/articles/PMC7215177/ http://dx.doi.org/10.1007/978-3-030-48641-9_11 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Pucha, Sai Naveen
Paruchuri, Praveen
Inferring Personality Types for Better Automated Negotiation
title Inferring Personality Types for Better Automated Negotiation
title_full Inferring Personality Types for Better Automated Negotiation
title_fullStr Inferring Personality Types for Better Automated Negotiation
title_full_unstemmed Inferring Personality Types for Better Automated Negotiation
title_short Inferring Personality Types for Better Automated Negotiation
title_sort inferring personality types for better automated negotiation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215177/
http://dx.doi.org/10.1007/978-3-030-48641-9_11
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