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Zhaoshuai Liu

dblp:269/4510 · DBLP profile ↗
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2ranked-venue papers
2as first author
1since 2021 · last 2023
0000-0002-8508-5482ORCID · corroborated

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

Artificial intelligence and machine learning · 2 · 2 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 2 · 2 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
Knowledge representation and reasoning · 50% Multi-agent systems · 50%
Theoretical computer science
1 paper
Logic in computer science · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Multi-agent systems › multi-agent reasoning
alternating-time temporal logic
0.412020
A Modal Logic for Joint Abilities under Strategy Commitments · IJCAI 2020
Knowledge, reasoning and agents › Knowledge representation and reasoning
logic-based reasoning
0.412020
A Modal Logic for Joint Abilities under Strategy Commitments · IJCAI 2020
Knowledge, reasoning and agents › Knowledge representation and reasoning › logic in computer science › logical foundations › non-classical logics › epistemic logic
modal logic
0.412020
A Modal Logic for Joint Abilities under Strategy Commitments · IJCAI 2020
Knowledge, reasoning and agents › Multi-agent systems › game theory
strategic ability
0.412020
A Modal Logic for Joint Abilities under Strategy Commitments · IJCAI 2020
Logic in computer science › modal logic
dynamic logic
0.112020
A Modal Logic for Joint Abilities under Strategy Commitments · IJCAI 2020

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

model checking · 0.9linear dynamic logic · 0.9
YearPublicationVenuePosition
2023 Epistemic JAADL: A Modal Logic for Joint Abilities with Imperfect Information
abstract
Coordination and joint ability are important problems in representation and reasoning about multi-agent systems. Ghaderi et al. presented a formalization of joint ability of coalitions in the expressive first-order language of the situation calculus. Essentially, a coalition has joint ability to achieve a goal if after iterated elimination of dominated strategies, any remaining joint strategy achieves the goal. Based on their work, Liu et al. proposed JAADL, a modal logic for joint abilities under strategy commitments. In this paper, we propose EJAADL, an epistemic extension of JAADL, for imperfect information games where agents may have incomplete knowledge or even false beliefs about the world. Like Ghaderi et al.’s work, elimination of dominated strategies is now based on beliefs about the world, rather than facts about the world as in JAADL. Strategies are required to be uniform, i.e., they select the same action in all accessible histories. We illustrate EJAADL with examples, analyze its properties, and show that model checking memoryless EJAADL is in EXPTIME. Moreover, we consider the fragment of EJAADL without the iterated elimination operator, and show that model-checking the memoryless version of this fragment can be done in PSPACE.
Zhaoshuai Liu, Aiting Liang, Yongmei Liu 0001
ECAI1
2020 A Modal Logic for Joint Abilities under Strategy Commitments
abstract
Representation and reasoning about strategic abilities has been an active research area in AI and multi-agent systems. Many variations and extensions of alternating-time temporal logic ATL have been proposed. However, most of the logical frameworks ignore the issue of coordination within a coalition, and are unable to specify the internal structure of strategies. In this paper, we propose JAADL, a modal logic for joint abilities under strategy commitments, which is an extension of ATL. Firstly, we introduce an operator of elimination of (strictly) dominated strategies, with which we can represent joint abilities of coalitions. Secondly, our logic is based on linear dynamic logic (LDL), an extension of linear temporal logic (LTL), so that we can use regular expressions to represent commitments to structured strategies. We analyze valid formulas in JAADL, give sufficient/necessary conditions for joint abilities, and show that model checking memoryless JAADL is in EXPTIME.
Zhaoshuai Liu, Liping Xiong, Yongmei Liu 0001, Yves Lespérance, Ronghai Xu, Hongyi Shi
IJCAI1