2 citations · 3 across the 6 of their papers we have counts for
3 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-Agent Planning with Spatio-Temporal and Topological Constraints using STL-GO
Sheryl Paul, Vidisha Kudalkar, Anand Balakrishnan +3
Multi-agent planning problems arise in a variety of engineering applications, such as multi-robot wildfire fighting and unmanned aerial inspection in factories. A particular challe…
Epistemic Exploration for Generalizable Planning and Learning in Non-Stationary Settings
Rushang Karia, Pulkit Verma, Alberto Speranzon +1
This paper introduces a new approach for continual planning and model learning in relational, non-stationary stochastic environments. Such capabilities are essential for the deploy…