Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/79426
Título: | A low-cost human-robot negotiation system |
Autor(es): | Rincon, Jaime Andres Costa, Ângelo Gonçalo Araújo Silva Julian, Vicente Carrascosa, Carlos Novais, Paulo |
Palavras-chave: | Assistant robot Automated negotiation EDGE AI Emotion detection |
Data: | Jan-2021 |
Editora: | Springer, Cham |
Revista: | Communications in Computer and Information Science |
Citação: | Rincon, J.A., Costa, A., Julian, V., Carrascosa, C., Novais, P. (2021). A Low-Cost Human-Robot Negotiation System. In: De La Prieta, F., El Bolock, A., Durães, D., Carneiro, J., Lopes, F., Julian, V. (eds) Highlights in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection. PAAMS 2021. Communications in Computer and Information Science, vol 1472. Springer, Cham. https://doi.org/10.1007/978-3-030-85710-3_26 |
Resumo(s): | In this paper we present a platform composed of a low-cost robot and a multi-agent system that uses deep learning algorithms, whose objective is to establish a negotiation process and persuasively sell items, maximising their price, thus gain. To this, we have focused on developing an interactive process that is able to interact with humans using a camera, microphone and speaker, to establish all negotiation process without physical contact. This is relevant due to the current COVID-19 situation and arisen issues of human contact. Validation processes with university students have revealed high interest and success in products’ negotiation. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/79426 |
ISBN: | 978-3-030-85709-7 |
e-ISBN: | 978-3-030-85710-3 |
DOI: | 10.1007/978-3-030-85710-3_26 |
ISSN: | 1865-0929 |
Versão da editora: | https://link.springer.com/chapter/10.1007/978-3-030-85710-3_26 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
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Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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low-cost_human-robot.pdf Acesso restrito! | 4,45 MB | Adobe PDF | Ver/Abrir |