5 citations · 5 across the 6 of their papers we have counts for
4 papers · 1 filter
Encoding formulas as deep networks: Reinforcement learning for zero-shot execution of LTL formulas
Yen-Ling Kuo, Boris Katz, Andrei Barbu
We demonstrate a reinforcement learning agent which uses a compositional recurrent neural network that takes as input an LTL formula and determines satisfying actions. The input LT…
Deep compositional robotic planners that follow natural language commands
Yen-Ling Kuo, Boris Katz, Andrei Barbu
We demonstrate how a sampling-based robotic planner can be augmented to learn to understand a sequence of natural language commands in a continuous configuration space to move and…
Temporal Grounding Graphs for Language Understanding with Accrued Visual-Linguistic Context
Rohan Paul, Andrei Barbu, Sue Felshin +2
A robot's ability to understand or ground natural language instructions is fundamentally tied to its knowledge about the surrounding world. We present an approach to grounding natu…
Deep sequential models for sampling-based planning
Yen-Ling Kuo, Andrei Barbu, Boris Katz
We demonstrate how a sequence model and a sampling-based planner can influence each other to produce efficient plans and how such a model can automatically learn to take advantage…