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Humboldt University of Berlin

Academic institutioneurope · de
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Research library294linked papers
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Selected work

Representative Papers

An Evolutionary Game With the Game Transitions Based on the Markov Process

Jan 01, 2024IEEE Transactions on Systems, Man, and Cybernetics: Systems

Traditional evolutionary game models neglect the role of individual psychological variability in shaping collective cooperation dynamics. Method: We propose a novel evolutionary game framework integrating Markovian game-state switching with reputation-guided neighbor selection on complex networks—first embedding stochastic game transitions into networked evolutionary dynamics and coupling them with a reputation-based mechanism for strategy updating. Contribution/Results: Theoretical analysis and numerical simulations reveal that both the game-switching rate and the reputation weight exert dual critical control over cooperation emergence. Increasing either parameter significantly enhances cooperative behavior, and high cooperation levels remain robust even in large-scale networks. This model establishes a computationally tractable theoretical paradigm for investigating the coevolution of psychological states, behavioral strategies, and network structure.

22 citationsRead paper

Open Data in the Digital Economy: An Evolutionary Game Theory Perspective

Jun 01, 2024IEEE Transactions on Computational Social Systems

Existing research on open data–driven sustainable development overlooks the critical role of data intermediaries—particularly regulatory entities—in governing data ecosystems. Method: This study constructs a tripartite evolutionary game model integrating data providers, users, and regulators—the first systematic incorporation of regulators into open data literature—to characterize multi-stakeholder co-evolutionary dynamics. It employs replicator dynamics analysis, numerical simulation, and sensitivity testing to examine nonlinear interactions among regulatory incentives, user costs, and data value. Contribution/Results: The analysis identifies multiple evolutionarily stable strategies (ESS) and quantifies threshold effects: regulatory reward-penalty intensity and users’ data mining capability exhibit nonlinear, bifurcation-like impacts on cooperation rates. Findings provide empirically grounded theoretical foundations for designing incentive-compatible platform mechanisms and evidence-based data governance policies to advance sustainable development through open data.

13 citationsRead paper

Towards a Theory on Process Automation Effects

Mar 25, 2025arXiv.org

Prior research predominantly focuses on the design and deployment of process automation, neglecting its real-world operational impacts after implementation. Method: This paper addresses this gap through a systematic literature review of human–machine collaboration, constructing the first theoretical framework specifically for *in-production* process automation. It proposes a novel four-part dynamic co-adaptation model—comprising technology, participants, managers, and developers—that transcends traditional binary (human/machine) analytical paradigms. Leveraging cross-domain theoretical integration and conceptual modeling, the study establishes a transferable framework for evaluating automation outcomes. Contribution/Results: The framework yields actionable pathways for organizational optimization of automation practices and identifies several novel research questions, thereby advancing a coherent, systemic research agenda for in-production automation in both academia and practice.

3 citationsRead paper

Structural Indexing of Relational Databases for the Evaluation of Free-Connex Acyclic Conjunctive Queries

Jan 08, 2026arXiv.org

This work proposes a novel indexing approach for the efficient evaluation of free-connex acyclic conjunctive queries (fc-ACQs) over relational databases, leveraging structural symmetries inherent in tuple data. By introducing an auxiliary database $D_{col}$ and employing a relation coloring refinement technique, the method constructs a compact structural index that enables linear-time preprocessing and constant-delay enumeration or counting. This is the first approach to exploit internal structural symmetries in relational data, departing from conventional value- or order-based indexing paradigms. The resulting index achieves significant compression on canonical structures such as binary trees and regular graphs—while maintaining worst-case linear size—and supports efficient evaluation of all fc-ACQs in time complexity strictly better than the size of the underlying database.

1 citationsRead paper

Escaping the Filter Bubble: Evaluating Electroencephalographic Theta Band Synchronization as Indicator for Selective Exposure in Online News Reading

Apr 25, 2025CHI Extended Abstracts

This study addresses the issue of selective exposure during online news consumption, which can lead users to become trapped in information cocoons. To identify this behavior in real time, the work proposes a novel multimodal neurophysiological marker that integrates eye-tracking and electroencephalography (EEG), specifically leveraging theta-band synchronization and gaze patterns. By simultaneously recording EEG theta power, eye movements, and participants’ attitude ratings toward news articles, the research reveals a significant positive correlation between parietal theta power and news认同度 (attitude alignment). This approach effectively captures the neural mechanisms underlying selective exposure and offers a quantifiable, real-time pathway toward mitigating the formation of information cocoons.

1 citationsRead paper
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