CLeaR 2022

The First International Workshop on Combining Learning and Reasoning: Programming Languages, Formalisms, and Representations
In conjunction with the 36th AAAI conference on artificial intelligence (AAAI-2022), February 22-March 1, 2022, Vancouver, BC, Canada

Workshop Day: Feb 28th,
Location: Virtual Room Blue 5

Accepted Papers

A Hybrid Neuro-Symbolic approach for Text-Based Games using Inductive Logic Programming	Kinjal Basu, Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi, Kartik Talamadupula, Tim Klinger, Murray Campbell, Mrinmaya Sachan, Gopal Gupta
Combining Deep Learning and Reasoning for Address Detection in Unstructured Text Documents	Matthias Engelbach, Dennis Klau, Jens Drawehn, Maximilien Kintz
On the Explainability of Convolutional Layers for Multi-Class Problems	Joe Townsend, Mateusz Kudla, Agnieszka Raszkowska, Theodoros Kasiousmis
Learning Neuro-Symbolic Relational Transition Models for Bilevel Planning	Rohan Chitnis, Tom Silver, Joshua B. Tenenbaum, Tomas Perez, Leslie Pack Kaelbling
Best of Both Worlds: A Hybrid Approach for Multi-Hop Explanation with Declarative Facts	Shane Storks, Qiaozi Gao, Aishwarya Naresh Reganti, Govind Thattai
Compositional Generalization and Neuro-Symbolic Architectures	Savitha Sam Abraham, Marjan Alirezaie
NeuroBE: NN Approximations to Bucket Elimination	Sakshi Agarwal, Kalev Kask, Alexander Ihler, Rina Dechter
Automatic Generation of Neural Architecture Search Spaces	David Calhas, Vasco M. Manquinho, Ines Lynce
A Confidence-Based Interface for Neuro-Symbolic Visual Question Answering	Thomas Eiter, Nelson Nicolas Higuera, Johannes Oetsch, Michael Pritz
Post-processing Counterexample-guided Fairness Guarantees in Neural Networks	Kiarash Mohammadi, Aishwarya Sivaraman, Golnoosh Farnadi
A Brain-Inspired Hierarchical Reasoning Framework for Cognition-Augmented Prosthetic Grasping	Laura Isabel Galindez Olascoaga, Alisha Menon, Mohamed Ibrahim, Jan Rabaey
Representing Prior Knowledge Using Randomly, Weighted Feature Networks for Visual Relationship Detection	Jinyung Hong, Ted Pavlic
Reinforcement Learning with General LTL Objectives is Intractable	Cambridge Yang, Michael Littman, Michael Carbin
FOLD-R++: A Toolset for Automated Inductive Learning of Default Theories from Mixed Data	Huaduo Wang, Gopal Gupta
Imposing Hard Logical Constraints on Multi-label Classification Neural Networks	Eleonora Giunchiglia, Thomas Lukasiewicz