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cs.AI2026
The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning
Agnese Chiatti, Michael Cochez, Cristina Cornelio +14
Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statistical approaches of neural n…
cs.AI2026
Multi-Objective Constraint Inference using Inverse reinforcement learning
Syed Ihtesham Hussain Shah, Floris den Hengst, Aneta Lisowska +1
Constraint inference is widely considered essential to align reinforcement learning agents with safety boundaries and operational guidelines by observing expert demonstrations. How…