2 papers
cs.AI2021
Learning Finite Linear Temporal Logic Specifications with a Specialized Neural Operator
Homer Walke, Daniel Ritter, Carl Trimbach +1
Finite linear temporal logic () is a powerful formal representation for modeling temporal sequences. We address the problem of learning a compact f…
cs.LG2019
Teaching with IMPACT
Carl Trimbach, Michael Littman
Like many problems in AI in their general form, supervised learning is computationally intractable. We hypothesize that an important reason humans can learn highly complex and vari…