410 citations · 441 across the 8 of their papers we have counts for
10 papers
Identifying Driver Interactions via Conditional Behavior Prediction
Ekaterina Tolstaya, Reza Mahjourian, Carlton Downey +3
Interactive driving scenarios, such as lane changes, merges and unprotected turns, are some of the most challenging situations for autonomous driving. Planning in interactive scena…
Composable Learning with Sparse Kernel Representations
Ekaterina Tolstaya, Ethan Stump, Alec Koppel +1
We present a reinforcement learning algorithm for learning sparse non-parametric controllers in a Reproducing Kernel Hilbert Space. We improve the sample complexity of this approac…
Learning Connectivity for Data Distribution in Robot Teams
Ekaterina Tolstaya, Landon Butler, Daniel Mox +3
Many algorithms for control of multi-robot teams operate under the assumption that low-latency, global state information necessary to coordinate agent actions can readily be dissem…
Synthesizing Decentralized Controllers with Graph Neural Networks and Imitation Learning
Fernando Gama, Qingbiao Li, Ekaterina Tolstaya +2
Dynamical systems consisting of a set of autonomous agents face the challenge of having to accomplish a global task, relying only on local information. While centralized controller…
Multi-Robot Coverage and Exploration using Spatial Graph Neural Networks
Ekaterina Tolstaya, James Paulos, Vijay Kumar +1
The multi-robot coverage problem is an essential building block for systems that perform tasks like inspection or search and rescue. We discretize the coverage problem to induce a…
Graph Neural Networks for Decentralized Controllers
Fernando Gama, Ekaterina Tolstaya, Alejandro Ribeiro
Dynamical systems comprised of autonomous agents arise in many relevant problems such as multi-agent robotics, smart grids, or smart cities. Controlling these systems is of paramou…
Graph Policy Gradients for Large Scale Robot Control
Arbaaz Khan, Ekaterina Tolstaya, Alejandro Ribeiro +1
In this paper, we consider the problem of learning policies to control a large number of homogeneous robots. To this end, we propose a new algorithm we call Graph Policy Gradients…
Inverse Optimal Planning for Air Traffic Control
Ekaterina Tolstaya, Alejandro Ribeiro, Vijay Kumar +1
We envision a system that concisely describes the rules of air traffic control, assists human operators and supports dense autonomous air traffic around commercial airports. We dev…
Learning Decentralized Controllers for Robot Swarms with Graph Neural Networks
Ekaterina Tolstaya, Fernando Gama, James Paulos +3
We consider the problem of finding distributed controllers for large networks of mobile robots with interacting dynamics and sparsely available communications. Our approach is to l…
Nonparametric Stochastic Compositional Gradient Descent for Q-Learning in Continuous Markov Decision Problems
Alec Koppel, Ekaterina Tolstaya, Ethan Stump +1
We consider Markov Decision Problems defined over continuous state and action spaces, where an autonomous agent seeks to learn a map from its states to actions so as to maximize it…