•  43
    Logic for Describing Strong Belief-Disagreement Between Agents
    with Tianqun Pan
    Studia Logica 106 (1): 35-47. 2018.
    The result of an interaction is influenced by its epistemic state, and several epistemic notions are related to multiagent situations. Strong belief-disagreement on a certain proposition between agents means that one agent believes the proposition and the other believes its negation. This paper presents a logical system describing strong belief-disagreement between agents and demonstrates its soundness and completeness. The notion of belief-disagreement as well as belief-agreement can facilitate…Read more
  •  29
    Logics for Moderate Belief-Disagreement Between Agents
    with Tianqun Pan
    Studia Logica 107 (3): 559-574. 2019.
    A moderate belief-disagreement between agents on proposition p means that one agent believes p and the other agent does not. This paper presents two logical systems, \ and \, that describe moderate belief-disagreement, and shows, using possible worlds semantics, that \ is sound and complete with respect to arbitrary frames, and \ is sound and complete with respect to serial frames. Syntactically, the logics are monomodal, but two doxastic accessibility relations are involved in their semantics. …Read more
  •  2
    Log Pattern Mining for Distributed System Maintenance
    with Peng Wang, Shiqing Du, and Wei Wang
    Complexity 2020 1-12. 2020.
    Due to the complexity of the network structure, log analysis is usually necessary for the maintenance of network-based distributed systems since logs record rich information about the system behaviors. In recent years, numerous works have been proposed for log analysis; however, they ignore temporal relationships between logs. In this paper, we target on the problem of mining informative patterns from temporal log data. We propose an approach to discover sequential patterns from event sequences …Read more