Artificial Intelligence

Papers
(The H4-Index of Artificial Intelligence is 27. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2022-05-01 to 2026-05-01.)
ArticleCitations
Online learning in sequential Bayesian persuasion: Handling unknown priors234
Editorial Board118
Primarily about primaries112
Drawing a map of elections111
A computational model of Ostrom's Institutional Analysis and Development framework100
Polynomial combined first-order rewritings for linear and guarded existential rules93
Diagnosis of intermittent faults in Multi-Agent Systems: An SFL approach69
Editorial Board66
Iterative voting with partial preferences65
Mitigating robust overfitting via self-residual-calibration regularization65
Transfer learning for collaborative recommendation with biased and unbiased data61
Knowledge-driven profile dynamics60
The distortion of distributed metric social choice58
No free lunch theorem for privacy-preserving LLM inference56
An α-regret analysis of adversarial bilateral trade54
Risk-averse autonomous systems: A brief history and recent developments from the perspective of optimal control49
(1+1) genetic programming with functionally complete instruction sets can evolve Boolean conjunctions and disjunctions with arbitrarily small error48
Epistemic planning: Perspectives on the special issue48
Estimating possible causal effects with latent variables via adjustment and novel rule orientation46
Weighted EF1 allocations for indivisible chores37
Learning MAX-SAT from contextual examples for combinatorial optimisation35
Defense coordination in security games: Equilibrium analysis and mechanism design34
Manipulation and peer mechanisms: A survey34
SensorSCAN: Self-supervised learning and deep clustering for fault diagnosis in chemical processes32
Hyper-heuristics for personnel scheduling domains28
Accurate parameter estimation for safety-critical systems with unmodeled dynamics28
GoSafeOpt: Scalable safe exploration for global optimization of dynamical systems27
Multi-objective reinforcement learning for provably incentivising alignment with value systems27
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