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Knowledge & Reasoning

3,940 papers (1 classified directly here)

Subtopics

Reasoning (2,428) Representation (1,906)

Papers per year

17
13
418
543
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Papers (including subtopics)

Hybrid State Representation for Video Procedure Planning WACV 2026
Relational Verification for Cost-Aware Quantum Program Optimization AAAI 2026
Automata-less Monitoring via Trace-Checking AAAI 2026
2-ASP(Q) Solving Based on CEGAR AAAI 2026
Strategic Reasoning over Golog Programs in the Nondeterministic Situation Calculus AAAI 2026
Extending Description Logics with Generic Concepts – the Case of Terminologies AAAI 2026
Enumerating Minimal Unsatisfiable Cores of LTLf Formulae AAAI 2026
Tractable Weighted First-Order Model Counting with Bounded Treewidth Binary Evidence AAAI 2026
A Logical Analysis of an Information Filtering Architecture Based on Epistemic Trust Inference AAAI 2026
Rational Revision of Group Intentions AAAI 2026
Model Change for Description Logic Concepts AAAI 2026
Self-Supervised Inductive Logic Programming AAAI 2026
Convergent Semantics for Weighted Bipolar Argumentation AAAI 2026
Incremental Maintenance of DatalogMTL Materialisations AAAI 2026
Horizontal and Vertical Federated Causal Structure Learning via Higher-order Cumulants AAAI 2026
Causal Discovery from Interval-Based Event Sequences AAAI 2026
Spatio-Temporal Hierarchical Causal Models AAAI 2026
A Causal Target for Learning to Defer Under Hidden Confounding AAAI 2026
Breaking the Dyadic Barrier: Rethinking Fairness in Link Prediction Beyond Demographic Parity AAAI 2026
I-CAM-UV: Integrating Causal Graphs over Non-Identical Variable Sets Using Causal Additive Models with Unobserved Variables AAAI 2026
Experimentation on Endogenous Graphs AAAI 2026
An Epistemic Perspective on Agent Awareness AAAI 2026
Symmetries and Other Variations of “End-Recursive” HTN Problems: Mapping the Border Between Decidable and Undecidable Restrictions AAAI 2026
Causal Inference Under Threshold Manipulation: Bayesian Mixture Modeling and Heterogeneous Treatment Effects AAAI 2026
Debiasing Machine Learning Predictions for Causal Inference Without Additional Ground Truth Data: “One Map, Many Trials” in Satellite-Driven Poverty Analysis AAAI 2026