Demo Data from VLDB 2026 / reviewers in the wild / expert
Jeremy Kong
dblp:199/6472
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, 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
1 paper |
Automated reasoning and model checking · 77% Logic in computer science · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Automated reasoning and model checking › model checking
multi-agent system verification |
0.3 | 1 | 2017 | Model Checking Multi-Agent Systems against LDLK Specifications · IJCAI 2017 |
Logic in computer science
epistemic logic |
0.1 | 1 | 2017 | Model Checking Multi-Agent Systems against LDLK Specifications · IJCAI 2017 |
Methods — techniques the papers use, named apart from their topics
symbolic model checking · 0.3alternating automata · 0.3OBDD · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Model Checking Multi-Agent Systems against LDLK SpecificationsabstractWe define the logic LDLK, a formalism for specifying multi-agent systems. LDLK extends LDL with epistemic modalities, including common knowledge, for reasoning about the evolution of knowledge states of the agents in the system. We study the complexity of verifying a multi-agent system against LDLK specifications and show this to be in PSPACE. We give an algorithm for the practical verification of multi-agent systems specified in LDLK. We show that the model checking algorithm, based on alternating-automata and nFA, is amenable to symbolic implementation on OBDDs. We introduce MCMAS LDLK , an extension of the open-source model checker MCMAS, implementing the algorithm and discuss the experimental results obtained. Jeremy Kong, Alessio Lomuscio |
IJCAI | 1 |