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dc.contributor.author
Kröhling, Dan Ezequiel
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dc.contributor.author
Chiotti, Omar Juan Alfredo
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dc.contributor.author
Martínez, Ernesto Carlos
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dc.date.available
2024-04-12T10:16:58Z
dc.date.issued
2023-04
dc.identifier.citation
Kröhling, Dan Ezequiel; Chiotti, Omar Juan Alfredo; Martínez, Ernesto Carlos; Artificial Theory of Mind in contextual automated negotiations within peer-to-peer markets; Pergamon-Elsevier Science Ltd; Engineering Applications Of Artificial Intelligence; 120; 4-2023; 1-20
dc.identifier.issn
0952-1976
dc.identifier.uri
http://hdl.handle.net/11336/232796
dc.description.abstract
With the advent of the sharing economy (eBay, Airbnb, Uber) and peer-to-peer electricity markets, negotiation agents become key to automate trading between prosumers. To be competitive, agents need to develop models of their opponents? strategic behavior depending on contextual circumstances. However, existent approaches do not account for others? ways of reasoning about how the context influences opponents? strategies. In this work, negotiation agents are endowed with artificial Theory of Mind (aToM) to represent mental states of others. Those states include their strategies, beliefs, the context influencing beliefs and the beliefs they may have about the beliefs others have about themselves depending on the context. From prior knowledge that relates private and contextual states with opponent´s plausible strategies, agents build models of different orders of aToM using weighted Gaussian Processes with heteroscedastic noise and adapt their strategies. During a negotiation episode, each agent selects the order of aToM that best accounts for its opponent´s counteroffers based on Bayesian surprise. To assess the proposed approach, a benchmark Smart Grid is used, where energy prosumers negotiate on a peer-to-peer basis to compensate for their energy deficits and sell their surpluses. Results obtained highlight that low orders of aToM increase social welfare at least in a 54% despite the selfish nature of prosumers. Also, more sophisticated aToM abilities increase the individual competitiveness of agents. This is the first work in the related literature that adds aToM abilities to negotiation agents while considering the negotiation context.
dc.format
application/pdf
dc.language.iso
eng
dc.publisher
Pergamon-Elsevier Science Ltd
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dc.rights
info:eu-repo/semantics/restrictedAccess
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.subject
ARTIFICIAL THEORY OF MIND
dc.subject
AUTOMATED NEGOTIATION
dc.subject
BAYESIAN SURPRISE
dc.subject
CONTEXT-AWARENESS
dc.subject
SMART GRIDS
dc.subject.classification
Ciencias de la Computación
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dc.subject.classification
Ciencias de la Computación e Información
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dc.subject.classification
CIENCIAS NATURALES Y EXACTAS
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dc.title
Artificial Theory of Mind in contextual automated negotiations within peer-to-peer markets
dc.type
info:eu-repo/semantics/article
dc.type
info:ar-repo/semantics/artículo
dc.type
info:eu-repo/semantics/publishedVersion
dc.date.updated
2024-04-10T12:21:37Z
dc.journal.volume
120
dc.journal.pagination
1-20
dc.journal.pais
Estados Unidos
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dc.description.fil
Fil: Kröhling, Dan Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
dc.description.fil
Fil: Chiotti, Omar Juan Alfredo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
dc.description.fil
Fil: Martínez, Ernesto Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentina
dc.journal.title
Engineering Applications Of Artificial Intelligence
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dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S0952197623000714
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.engappai.2023.105887
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