Grants and Contributions:
Title:
Continuous action, time, and space (CATS) reinforcement learning
Agreement Number:
962712
Agreement Value:
$199,870.00
Agreement Date:
Dec 17, 2020 - Sep 1, 2024
Description:
The ability of an autonomous system to usefully adapt and learn online is a desirable goal for any autonomous vehicle project, especially in terms of the AI-enabled autonomous transportation of goods in obstacle-rich environments. Furthermore, any vision for autonomy project needs decision-making systems to make use of that visual information. This Project will research, develop and demonstrate autonomous vehicle-based algorithms and decision-making systems that could be deployed on autonomous vehicles such as unmanned aircraft systems. While there are autonomous decision-making and reinforcement learning algorithms under active development in the research community, there are two reasons for
undertaking this specific Project. First, no one has ever applied the new Legendre Memory Units (LMU) temporal representation system to this task, and the LMU has been shown to produce orders of magnitude of improvement over traditional
methods. Second, the computation system resulting from these methods could likely
be efficiently implemented in modern hardware, including GPUs, TPUs, and
neuromorphic computation.
Organization:
National Research Council Canada
Expected Results:
In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.
Location:
Waterloo, Ontario, CA N2L 3G1
Reference Number:
172-2020-2021-Q3-962712
Agreement Type:
Grant
Report Type:
Grants and Contributions
Recipient Business Number:
119260685
Recipient Type:
Academia
Additional Information:
This agreement has been amended 1 time(s). The end date of this agreement has been modified by 365 days.
Amendment Date
Aug 17, 2023
Recipient's Legal Name:
University of Waterloo
Federal Riding Name:
Waterloo
Federal Riding Number:
35112
Program:
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Purpose:
Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.
NAICS Code:
541710
Amendments: