41 citations · 92 across the 8 of their papers we have counts for
8 papers
Learning Norms via Natural Language Teachings
Taylor Olson, Ken Forbus
To interact with humans, artificial intelligence (AI) systems must understand our social world. Within this world norms play an important role in motivating and guiding agents. How…
Analogical Learning in Tactical Decision Games
Tom Hinrichs, Greg Dunham, Ken Forbus
Tactical Decision Games (TDGs) are military conflict scenarios presented both textually and graphically on a map. These scenarios provide a challenging domain for machine learning…
Neural Analogical Matching
Maxwell Crouse, Constantine Nakos, Ibrahim Abdelaziz +1
Analogy is core to human cognition. It allows us to solve problems based on prior experience, it governs the way we conceptualize new information, and it even influences our visual…
Improving Graph Neural Network Representations of Logical Formulae with Subgraph Pooling
Maxwell Crouse, Ibrahim Abdelaziz, Cristina Cornelio +4
Recent advances in the integration of deep learning with automated theorem proving have centered around the representation of logical formulae as inputs to deep learning systems. I…
Mapping Natural-language Problems to Formal-language Solutions Using Structured Neural Representations
Kezhen Chen, Qiuyuan Huang, Hamid Palangi +3
Generating formal-language programs represented by relational tuples, such as Lisp programs or mathematical operations, to solve problems stated in natural language is a challengin…
High-Fidelity Vector Space Models of Structured Data
Maxwell Crouse, Achille Fokoue, Maria Chang +6
Machine learning systems regularly deal with structured data in real-world applications. Unfortunately, such data has been difficult to faithfully represent in a way that most mach…
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision (Short Version)
Chen Liang, Jonathan Berant, Quoc Le +2
Extending the success of deep neural networks to natural language understanding and symbolic reasoning requires complex operations and external memory. Recent neural program induct…
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision
Chen Liang, Jonathan Berant, Quoc Le +2
Harnessing the statistical power of neural networks to perform language understanding and symbolic reasoning is difficult, when it requires executing efficient discrete operations…