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Thalya Fossey

dblp:415/3493 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Multi-agent systems · 75% Knowledge representation and reasoning · 25%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning
argumentation
0.912025
Argument-based Multi-Issue Negotiation · IJCAI 2025
Knowledge, reasoning and agents › Multi-agent systems › automated negotiation
argument-based negotiation
0.912025
Argument-based Multi-Issue Negotiation · IJCAI 2025
Knowledge, reasoning and agents › Multi-agent systems
automated negotiation
0.912025
Argument-based Multi-Issue Negotiation · IJCAI 2025
Knowledge, reasoning and agents › Multi-agent systems › automated negotiation
multi-issue negotiation
0.912025
Argument-based Multi-Issue Negotiation · IJCAI 2025

Methods — techniques the papers use, named apart from their topics

utility modeling · 0.9concession mechanism · 0.9
YearPublicationVenuePosition
2025 Argument-based Multi-Issue Negotiation
abstract
Automated negotiation aims at finding agreements between agents with conflicting goals. Existing utility-based approaches guarantee agents satisfaction with negotiation outcomes, especially in multi-issue negotiations where concession mechanisms lead to win-win results. However, they lack explainability and do not consider agents’ beliefs. On the other hand, argument-based approaches provide reasons for accepting or rejecting offers but do not include utility modeling for offers or enable concession mechanisms in multi-issue settings. We propose a novel hybrid approach combining both types of approaches. The utility-based component enables agents to make concessions on complex negotiation objects to achieve win-win outcomes, while the argumentation component ensures that accepted offers align with the agents' personal argumentation theories. These theories represent their beliefs, encoding various profiles, ethical considerations, social norms, or legal principles.
Thalya Fossey, Jean-Guy Mailly, Pavlos Moraitis
IJCAI1