Improving Safety in Reinforcement Learning Using Model-Based Architectures and Human Intervention. - Bharat Prakash; Mohit Khatwani; Nicholas R. Waytowich; Tinoosh Mohsenin (FLAIRS, 2019)

On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning. - Bharat Prakash; Mark Horton; Nicholas R. Waytowich; William David Hairston; Tim Oates 001; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2019)

Guiding Safe Reinforcement Learning Policies Using Structured Language Constraints. - Bharat Prakash; Nicholas R. Waytowich; Ashwinkumar Ganesan; Tim Oates 001; Tinoosh Mohsenin (SafeAI@AAAI, 2020)

Energy-Efficient Hardware for Language Guided Reinforcement Learning. - Aidin Shiri; Arnab Neelim Mazumder; Bharat Prakash; Nitheesh Kumar Manjunath; Houman Homayoun; Avesta Sasan; Nicholas R. Waytowich; Tinoosh Mohsenin (ACM Great Lakes Symposium on VLSI, 2020)

Neural Networks for Pulmonary Disease Diagnosis using Auditory and Demographic Information. - Morteza Hosseini; Haoran Ren; Hasib-Al Rashid; Arnab Neelim Mazumder; Bharat Prakash; Tinoosh Mohsenin (CoRR, 2020)

An Energy-Efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. - Aidin Shiri; Bharat Prakash; Arnab Neelim Mazumder; Nicholas R. Waytowich; Tim Oates 001; Tinoosh Mohsenin (AICAS, 2021)

Retrospective on the 2021 MineRL BASALT Competition on Learning from Human Feedback. - Rohin Shah; Steven H. Wang; Cody Wild; Stephanie Milani; Anssi Kanervisto; Vinicius G. Goecks; Nicholas R. Waytowich; David Watkins-Valls; Bharat Prakash; Edmund Mills; Divyansh Garg; Alexander Fries; et al. (NeurIPS (Competition and Demos), 2021)

Interactive Hierarchical Guidance using Language. - Bharat Prakash; Nicholas R. Waytowich; Tim Oates 001; Tinoosh Mohsenin (CoRR, 2021)

Automatic Goal Generation using Dynamical Distance Learning. - Bharat Prakash; Nicholas R. Waytowich; Tinoosh Mohsenin; Tim Oates 001 (CoRR, 2021)

Combining Learning from Human Feedback and Knowledge Engineering to Solve Hierarchical Tasks in Minecraft. - Vinicius G. Goecks; Nicholas R. Waytowich; David Watkins; Bharat Prakash (CoRR, 2021)

An Energy Efficient EdgeAI Autoencoder Accelerator for Reinforcement Learning. - Nitheesh Kumar Manjunath; Aidin Shiri; Morteza Hosseini; Bharat Prakash; Nicholas R. Waytowich; Tinoosh Mohsenin (IEEE Open J. Circuits Syst., 2021)

Cyclic Sparsely Connected Architectures for Compact Deep Convolutional Neural Networks. - Morteza Hosseini; Nitheesh Kumar Manjunath; Bharat Prakash; Arnab Neelim Mazumder; Vandana Chandrareddy; Houman Homayoun; Tinoosh Mohsenin (IEEE Trans. Very Large Scale Integr. Syst., 2021)

Combining Learning From Human Feedback and Knowledge Engineering to Solve Hierarchical Tasks in Minecraft. - Vinicius G. Goecks; Nicholas R. Waytowich; David Watkins-Valls; Bharat Prakash (AAAI Spring Symposium: MAKE, 2022)

Retrospective on the 2021 BASALT Competition on Learning from Human Feedback. - Rohin Shah; Steven H. Wang; Cody Wild; Stephanie Milani; Anssi Kanervisto; Vinicius G. Goecks; Nicholas R. Waytowich; David Watkins-Valls; Bharat Prakash; Edmund Mills; Divyansh Garg; Alexander Fries; et al. (CoRR, 2022)

Towards an Interpretable Hierarchical Agent Framework using Semantic Goals. - Bharat Prakash; Nicholas R. Waytowich; Tim Oates 001; Tinoosh Mohsenin (CoRR, 2022)

A Hardware Accelerator for Language-Guided Reinforcement Learning. - Aidin Shiri; Arnab Neelim Mazumder; Bharat Prakash; Houman Homayoun; Nicholas R. Waytowich; Tinoosh Mohsenin (IEEE Des. Test, 2022)

E2HRL: An Energy-efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning. - Aidin Shiri; Uttej Kallakuri; Hasib-Al Rashid; Bharat Prakash; Nicholas R. Waytowich; Tim Oates 001; Tinoosh Mohsenin (ACM Trans. Design Autom. Electr. Syst., 2022)

ReProHRL: Towards Multi-Goal Navigation in the Real World using Hierarchical Agents. - Tejaswini Manjunath; Mozhgan Navardi; Prakhar Dixit; Bharat Prakash; Tinoosh Mohsenin (CoRR, 2023)

LLM Augmented Hierarchical Agents. - Bharat Prakash; Tim Oates 001; Tinoosh Mohsenin (CoRR, 2023)

Using LLMs for Augmenting Hierarchical Agents with Common Sense Priors. - Bharat Prakash; Tim Oates 001; Tinoosh Mohsenin (FLAIRS, 2024)