Demo Data from EDBT 2026 / reviewers in the wild / expert
Sefi Erlich
dblp:220/3487
· DBLP profile ↗
3ranked-venue papers
1as first author
2since 2021 · last 2024
0000-0003-0773-5758ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 first-author · 1 since 2021Computer networks · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author
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.
| Theoretical computer science
2 papers |
Algorithmic game theory and mechanism design · 100% | |
| Artificial intelligence
1 paper |
Multi-agent systems · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Multi-agent systems
automated negotiation |
0.8 | 1 | 2024 | Negotiation strategies for agents with ordinal preferences: Theoretical analysis and human study · Artif. Intell. 2024 |
Algorithmic game theory and mechanism design › social choice
ordinal preferences |
0.6 | 2 | 2024 | Negotiation Strategies for Agents with Ordinal Preferences · IJCAI 2018 Negotiation strategies for agents with ordinal preferences: Theoretical analysis and human study · Artif. Intell. 2024 |
Algorithmic game theory and mechanism design
negotiation |
0.3 | 1 | 2018 | Negotiation Strategies for Agents with Ordinal Preferences · IJCAI 2018 |
Algorithmic game theory and mechanism design › cooperative game theory
bargaining |
0.1 | 1 | 2018 | Negotiation Strategies for Agents with Ordinal Preferences · IJCAI 2018 |
Methods — techniques the papers use, named apart from their topics
subgame perfect equilibrium · 0.3distribution-free solution concepts · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Negotiation strategies for agents with ordinal preferences: Theoretical analysis and human study
Noam Hazon, Sefi Erlich, Ariel Rosenfeld, Sarit Kraus |
Artif. Intell. | 2 |
| 2021 | Heterogeneous SDN controller placement problem - The Wi-Fi and 4G LTE-U case
Aviram Zilberman, Yoram Haddad 0001, Sefi Erlich, Yossi Peretz, Amit Dvir |
Comput. Networks | 3 |
| 2018 | Negotiation Strategies for Agents with Ordinal PreferencesabstractNegotiation is a very common interaction between automated agents. Many common negotiation protocols work with cardinal utilities, even though ordinal preferences, which only rank the outcomes, are easier to elicit from humans. In this work we concentrate on negotiation with ordinal preferences over a finite set of outcomes. We study an intuitive protocol for bilateral negotiation, where the two parties make offers alternately. We analyze the negotiation protocol under different settings. First, we assume that each party has full information about the other party's preference order. We provide elegant strategies that specify a sub-game perfect equilibrium for the agents. We further show how the studied negotiation protocol almost completely implements a known bargaining rule. Finally, we analyze the no information setting. We study several solution concepts that are distribution-free, and analyze both the case where neither party knows the preference order of the other party, and the case where only one party is uninformed. Sefi Erlich, Noam Hazon, Sarit Kraus |
IJCAI | 1 |