Publications
2019
Gabriel V. de la Cruz Jr. Accelerate the Learning Speed of Deep Reinforcement Learning by Pre-training with Non-expert Human Demonstrations. Washington State University, Master's Thesis. May 2019.
Gabriel V. de la Cruz Jr., Yunshu Du, and Matthew E. Taylor. Jointly Pre-training with Supervised, Autoencoder, and Value Losses for Deep Reinforcement Learning. In Proceedings of the Adaptive Learning Agents (ALA) workshop, Montreal, Canada, May 2019.
Gabriel V. de la Cruz Jr., Yunshu Du, and Matthew E. Taylor. Pre-training with Non-expert Human Demonstrations for Deep Reinforcement Learning. The Knowledge Engineering Review. ***Accepted***
Garrett Wilson, Christopher Pereyda, Nisha Raghunath, Gabriel V. de la Cruz Jr., Shivam Goel, Sepehr Nesaei, Bryan Minor, Maureen Schmitter-Edgecombe, Matthew E. Taylor, and Diane J. Cook. Robot-Enabled Support of Daily Activities in Smart Home Environments. Cognitive Systems Research, May 2019. [pdf]
2018
Gabriel V. de la Cruz Jr., Yunshu Du, and Matthew E. Taylor. Pre-training Neural Networks with Human Demonstrations for Deep Reinforcement Learning. In Proceedings of the Adaptive Learning Agents (ALA) workshop, Stockholm, Sweden, July 2018.
2017
Gabriel V. de la Cruz Jr., Yunshu Du, and Matthew E. Taylor. Pre-training Neural Networks with Human Demonstrations for Deep Reinforcement Learning. ArXiv 1709.04083, September 2017.
2016
David Isele, José Marcio Luna, Eric Eaton, Gabriel V. de la Cruz Jr., James Irwin, Brandon Kallaher, and Matthew E. Taylor. Lifelong Learning for Disturbance Rejection on Mobile Robots. In Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October 2016. 48% acceptance rate
*Yunshu Du, *Gabriel V. de la Cruz Jr., James Irwin, and Matthew E. Taylor. Initial Progress in Transfer for Deep Reinforcement Learning Algorithms. In Proceedings of Deep Reinforcement Learning: Frontiers and Challenges workshop (at IJCAI), New York City, NY, USA, July 2016. *contributed equally
David Isele, José Marcio Luna, Eric Eaton, Gabriel V. de la Cruz Jr., James Irwin, Brandon Kallaher, and Matthew E. Taylor. Work in Progress: Lifelong Learning for Disturbance Rejection on Mobile Robots. In Proceedings of the Adaptive Learning Agents (ALA) workshop (at AAMAS), Singapore, May 2016.
2015
Gabriel V. de la Cruz Jr., Bei Peng, Walter S. Lasecki, and Matthew E. Taylor. Towards Integrating Real-Time Crowd Advice with Reinforcement Learning. In The 20th ACM Conference on Intelligent User Interfaces (IUI), March 2015. Poster: 41% acceptance rate for poster submissions
Gabriel V. de la Cruz Jr., Bei Peng, Walter S. Lasecki, and Matthew E. Taylor. Generating Real-Time Crowd Advice to Improve Reinforcement Learning Agents. In Proceedings of the Learning for General Competency in Video Games workshop (AAAI), January 2015.
2014
Gabriel V. de la Cruz Jr., Gokcen Cilingir, Shira L. Broschat, Douglas R. Call, Margaret A.Davis, and Lisa H. Orfe. A rapid algorithm for detecting antibiotic resistance gene sequencesfrom next-gen sequencing data. Poster presented at the WSU Showcase for UndergraduateResearch and Creative Activities (SURCA), April 2014