4 papers · 1 filter
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…
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…
Successful Misunderstandings: Learning to Coordinate Without Being Understood
Nikolaos Kondylidis, Anil Yaman, Frank van Harmelen +2
The main approach to evaluating communication is by assessing how well it facilitates coordination. If two or more individuals can coordinate through communication, it is generally…
"Stop replacing salt with sugar!'': Towards Intuitive Human-Agent Teaching
Nikolaos Kondylidis, Andrea Rafanelli, Ilaria Tiddi +2
Humans quickly learn new concepts from a small number of examples. Replicating this capacity with Artificial Intelligence (AI) systems has proven to be challenging. When it comes t…