Jesse Hostetler

发表

Learning Probabilistic Behavior Models in Real-Time Strategy Games

Thomas G. Dietterich, Alan Fern, Jesse Hostetler, 2011, AIIDE.

Inferring Strategies from Limited Reconnaissance in Real-time Strategy Games

Thomas G. Dietterich, Alan Fern, Jesse Hostetler, 2012, UAI.

Monte Carlo Tree Search with Fixed and Adaptive State Abstractions

Jesse Hostetler, 2017 .

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

M. Gervasio, Jesse Hostetler, Eric Yeh, 2022, ArXiv.

A Framework for Understanding and Visualizing Strategies of RL Agents

Pedro M. N. Sequeira, M. Gervasio, Jesse Hostetler, 2022, ArXiv.

Conformal Prediction Intervals for Markov Decision Process Trajectories

Thomas G. Dietterich, Jesse Hostetler, 2022, ArXiv.

Global and Local Analysis of Interestingness for Competency-Aware Deep Reinforcement Learning

Pedro M. N. Sequeira, M. Gervasio, Jesse Hostetler, 2022, ArXiv.

Dynamically throttleable neural networks

B. Bhanu, Jesse Hostetler, S. Chai, 2022, Machine Vision and Applications.

System Design for an Integrated Lifelong Reinforcement Learning Agent for Real-Time Strategy Games

Tyler L. Hayes, Mustafa Burak Gurbuz, Sahana P Joshi, 2022, AIMLSystems.

Model-Free Generative Replay for Lifelong Reinforcement Learning: Application to Starcraft-2

Zachary A. Daniels, Ajay Divakaran, Jesse Hostetler, 2022, CoLLAs.

A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems

Santhosh K. Ramakrishnan, Gautam K. Vallabha, Praveen K. Pilly, 2023, Neural Networks.

Sample-Based Tree Search with Fixed and Adaptive State Abstractions

Thomas G. Dietterich, Alan Fern, Jesse Hostetler, 2017, J. Artif. Intell. Res..

Progressive Abstraction Refinement for Sparse Sampling

Thomas G. Dietterich, Alan Fern, Jesse Hostetler, 2015, UAI.

Bootstrapping Deep Neural Networks from Approximate Image Processing Pipelines

Sek Chai, Kilho Son, Jesse Hostetler, 2018, 2019 2nd Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications (EMC2).

Bootstrapping Deep Neural Networks from Image Processing and Computer Vision Pipelines pdf

Sek M. Chai, Kilho Son, Jesse Hostetler, 2018, ArXiv.

Generative Memory for Lifelong Reinforcement Learning pdf

Aswin Raghavan, Sek M. Chai, Jesse Hostetler, 2019, ArXiv.

M ODEL -F REE G ENERATIVE R EPLAY FOR L IFELONG R EINFORCEMENT L EARNING : A PPLICATION TO S TARCRAFT -2

Zachary A. Daniels, Ajay Divakaran, Jesse Hostetler, 2022 .

Lifelong Learning using Eigentasks: Task Separation, Skill Acquisition, and Selective Transfer pdf

Aswin Raghavan, Ajay Divakaran, Indranil Sur, 2020, ArXiv.

State Aggregation in Monte Carlo Tree Search

Thomas G. Dietterich, Alan Fern, Jesse Hostetler, 2014, AAAI.

Dynamically Throttleable Neural Networks (TNN) pdf

Bir Bhanu, Sek Chai, Samyak Parajuli, 2020, ArXiv.

Bootstrapping Deep Neural Networks from Approximate Image Processing Pipelines

Jesse Hostetler, S. Chai, Kilho Son, 2018, 2019 2nd Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications (EMC2).