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Home » Archives for Jesse Hostetler
Jesse Hostetler

Jesse Hostetler

Publications

Artificial intelligence publications August 17, 2022

A Framework for understanding and Visualizing Strategies of RL Agents

Pedro Sequeira, Jesse Hostetler, Melinda Gervasio

We present a framework for learning comprehensible models of sequential decision tasks in which agent strategies are characterized using temporal logic formulas.

Artificial intelligence publications July 1, 2022

Outcome-Guided Counterfactuals for Reinforcement Learning Agents from a Jointly Trained Generative Latent Space

Eric Yeh, Pedro Sequeira, Jesse Hostetler, Melinda Gervasio

We present a novel generative method for producing unseen and plausible counterfactual examples for reinforcement learning (RL) agents based upon outcome variables that characterize agent behavior.

Machine learning publications June 8, 2022

Conformal Prediction Intervals for Markov Decision Process Trajectories

Jesse Hostetler

This paper extends previous work on conformal prediction for functional data and conformalized quantile regression to provide conformal prediction intervals over the future behavior of an autonomous system executing a fixed control policy on a Markov Decision Process.

Machine learning publications June 8, 2022

Conformal Prediction Intervals for Markov Decision Process Trajectories

Jesse Hostetler

This paper extends previous work on conformal prediction for functional data and conformalized quantile regression to provide conformal prediction intervals over the future behavior of an autonomous system executing a fixed control policy on a Markov Decision Process (MDP).

Machine learning publications March 14, 2022

Model-Free Generative Replay For Lifelong Reinforcement Learning: Application To Starcraft-2

Jesse Hostetler, Michael Piacentino, Ajay Divakaran

We evaluate our proposed algorithms on three different scenarios comprising tasks from the Starcraft 2 and Minigrid domains.

Machine learning publications July 14, 2020

Lifelong learning using Eigentasks: Task separation, skill acquisition, and selective transfer

Ajay Divakaran, Jesse Hostetler

We introduce the eigentask framework for lifelong learning. An eigentask is a pairing of a skill that solves a set of related tasks, paired with a generative model that can sample from the skill’s input space.

Machine learning publications April 11, 2019

Toward Runtime Throttleable Neural Networks

Jesse Hostetler

This paper presents an approach to creating runtime-throttleable NNs that can adaptively balance performance and resource use in response to a control signal.

Machine learning publications January 30, 2019

Bootstrapping Deep Neural Networks from Image Processing and Computer Vision Pipelines

Jesse Hostetler

We intend to replace parts or all of a target pipeline with deep neural networks to achieve benefits such as increased accuracy or reduced computational requirement.

Machine learning publications January 21, 2019

Generative Memory for Lifelong Reinforcement Learning

Jesse Hostetler

Our research is focused on understanding and applying biological memory transfers to new AI systems that can fundamentally improve their performance, throughout their fielded lifetime experience.

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