Abstract
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.
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Acknowledgement
This work was partly supported by the Spanish Government (RTI2018-095390-B-C31) and Universitat Politecnica de Valencia Research Grant PAID-10-19.
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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
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