Projects

DeepStack

Principal Investigator
Michael Bowling

Problem we’re trying to solve

For several years, AI researchers have had a number of different techniques for predicting and planning optimal actions in situations of perfect information (where all actors have the same, full knowledge of the world). Techniques have been lacking for dealing with imperfect information situations (where actors do not have access to certain information or have access to information the other doesn’t). DeepStack seeks to successfully apply, for the first time, theoretical techniques for perfect information games into situations with imperfect information.

How will this help someone / an industry?

For computing scientists and AI researchers, DeepStack represents a foundational step forward in dealing with issues around predicting optimal actions in the face of ambiguity and uncertainty. The theoretical advancements demonstrated in DeepStack will open new avenues of research for scientists interested in building, and planning with, models of unknown, complex dynamic systems.

Type of MI used

Reinforcement learning, Deep learning

Projects

Advanced Analytics for Curling

Principal Investigator:
Michael Bowling

Problem we’re trying to solve

The Computer Curling Research Group focuses on deep analytics for the sport of curling for player analysis and system analysis, and to create tools that can translate AI discovered insights into improvements to human decision making.

How will this help someone / an industry?

The ultimate goal of this project is to develop tools and models that enable player/team assessment, strategic game modeling, and analytics for broadcast television.

Type of MI used

Deep learning, Search and Planning.