With diverse expertise in AI and machine learning, our researchers lead the world across many subfields and application spaces, including reinforcement learning, precision health, natural language processing, heuristic search and game theory.
Learning through experience
Amii researchers are pioneers and leaders in the field of reinforcement learning (RL), a branch of machine learning that enables AI systems to learn through experience. RL systems interact with their environments, often through trial and error, earning positive or negative rewards based on their actions. Humans define the overall task and relevant rewards that the system uses to discover the best action to take in a given situation.
Instead of being told what actions to take to achieve a goal, the system must learn which actions yield the most reward by trying them. Over time, the system develops a policy (or way of acting) that lets it select the action that will best achieve the goal, which can help us discover the optimal actions to take in a given scenario.
Reinforcement learning can be used for process optimization and improvement, as part of a recommender or intelligent tutoring system, and for adaptive control and decision making in autonomous systems.
Our teams conduct AI and machine learning research in a diverse range of subfields and application areas. Learn more about some of our key areas of impact below.
This branch of machine learning enables AI systems to learn to achieve goals through experience.
Foundational to many AI systems, this area of research increases the speed of a system by improving an algorithm’s ability to search for and find approximate solutions to a defined problem.
An AI application space, this area assists healthcare providers through individually tailored diagnosis, prognosis and treatment planning for physical and mental health.
At the intersection of computing science and linguistics, this research area focuses on understanding and improving how systems process and analyze human language.
This research area focuses on understanding and optimizing strategic interactions between individuals within an environment. It includes human interactions as well as game playing AI.
With applications such as computer vision, translation and classification systems, this branch of machine learning relies on a network of nodes for distributed information processing.
Within the field of AI, the study of robotics includes the development of control and sensor systems for autonomous and semi-autonomous mechanical systems.
Focusing on security, fairness and interpretability, researchers in this area work to improve AI systems and their interactions with humans and human systems.
With connections to graph theory, this research area develops techniques for analyzing, organizing and visualizing complex networks of interacting entities.
Research in this area focuses on developing and improving techniques for analyzing vast amounts of data and extracting useful information and insights.
Our academic scientists, based in Canada, teach and conduct research at some of the world’s top universities specializing in artificial intelligence and machine learning.
Mar 3rd 2023
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Feb 26th 2023
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Feb 9th 2023
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Oct 30th 2023
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Apr 3rd 2023
Business
Feb 6th 2023
Scientific research requires a collaborative community. We work with our partners in government, industry and academia to accelerate leading-edge advancements and forward-thinking solutions to some of the toughest challenges facing the world.
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