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Ruiqi Jin 0002

dblp:315/9419-2 · DBLP profile ↗
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2ranked-venue papers
2as first author
2since 2021 · last 2026
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 2 first-author · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-author · 2 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.

Theoretical computer science
2 papers
Logic in computer science · 65% Automated reasoning and model checking · 17% Computational complexity · 17%
Artificial intelligence
2 papers
Multi-agent systems · 65% Knowledge representation and reasoning · 35%

Topics — the 8 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Multi-agent systems › multi-agent reasoning
strategic reasoning
1.922026
Enhancing Strategy Logic with Procedural Rationality · AAAI 2026
A Modal Logic for Joint Abilities of Structured Strategies with Bounded Complexity · AAAI 2025
Knowledge, reasoning and agents › Knowledge representation and reasoning
rationality
1.012026
Enhancing Strategy Logic with Procedural Rationality · AAAI 2026
Automated reasoning and model checking
model checking
1.012026
Enhancing Strategy Logic with Procedural Rationality · AAAI 2026
Computational complexity › complexity of reasoning
model checking complexity
1.012026
Enhancing Strategy Logic with Procedural Rationality · AAAI 2026
Logic in computer science › modal logic › game logic
strategy logic
1.012026
Enhancing Strategy Logic with Procedural Rationality · AAAI 2026
Logic in computer science
temporal logic
1.012026
Enhancing Strategy Logic with Procedural Rationality · AAAI 2026
Logic in computer science › temporal logic › branching-time temporal logic
alternating-time temporal logic
0.912025
A Modal Logic for Joint Abilities of Structured Strategies with Bounded Complexity · AAAI 2025
Logic in computer science
modal logic
0.912025
A Modal Logic for Joint Abilities of Structured Strategies with Bounded Complexity · AAAI 2025

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

expressiveness proof · 2.0EXPTIME-completeness proof · 2.0norm synthesis · 1.7model checking · 1.7linear dynamic logic · 1.7
YearPublicationVenuePosition
2026 Enhancing Strategy Logic with Procedural Rationality
abstract
ATL and Strategy Logic (SL) are important languages for representation and reasoning about strategic abilities of coalitions in multi-agent systems. In analyzing strategies of agents in multi-agent systems, an important concept to consider is rationality. Strategy Logic can express rationality concepts such as Nash Equilibrium (NE). Recently, there has been work on logics for joint abilities incorporating rationality concepts based on iterated elimination of dominated strategies (IEDS). Each of NE and IEDS has its strengths and limitations. However, when the payoff is binary, e.g., whether a goal is satisfied, IEDS has more distinguishing power than NE. In this work, we propose Strategy Logic with IEDS (SL_{IEDS}), an extension of Strategy Logic with an IEDS operator, where we can reason about rational strategies that survive IEDS. We prove that SL_{IEDS} is strictly more expressive than SL. Finally, we prove that model checking memoryless SL_{IEDS} is EXPTIME-complete.
Ruiqi Jin 0002, Yongmei Liu 0001
AAAI1
2025 A Modal Logic for Joint Abilities of Structured Strategies with Bounded Complexity
abstract
Coordination and joint ability are important topics in representation and reasoning about multi-agent systems. The modal logic JAADL proposed by Liu et al. extends ATL with joint abilities, which enables reasoning about whether a coalition of agents can coordinate and achieve a goal without communication. However, like ATL, strategic abilities in JAADL are defined in terms of combinatorial strategies, which are functions from histories or states to actions. On the other hand, there has been research on reasoning about natural strategic abilities, where a natural strategy is formalized as a sequence of condition-action pairs, making it more human-friendly than combinatorial strategy. In this work, we propose SJAADL, a variation of JAADL where strategic abilities are defined in terms of structured strategies represented with LDL (linear dynamic logic) formulas, with bounded complexity. We use nondeterministic strategies since they are more expressive, natural and succinct than determinstic ones. We present syntax and semantics of SJAADL. We show that model checking SJAADL can be done in time quasi-polynomial with the model size, exponential with the formula size, and with the complexity bound of structured strategies, exponential in the memoryless case and double exponential in the memoryful case. Finally, we introduce the problem of synthesizing norms to achieve joint abilities, and give two algorithms for it.
Ruiqi Jin 0002, Yongmei Liu 0001, Liping Xiong
AAAI1