Action-Theoretic Formalization of Actual Causation and its Applications
Research on actual causality involves finding in a given log the actions or events that caused an observed effect. Causality analysis plays a crucial role in automated reasoning and has numerous applications in practically every field. For instance, if an aircraft crashes, it is useful to analyze the actions captured by the flight-recorder and identify those that led to this disaster. Philosophers since the time of Aristotle have been grappling with this basic question of what actually caused an effect, but a proper definition that is general enough is yet to be proposed. It turns out that actual causality in general is extremely tricky to formulate.
Current formal approaches to actual causation are based on Structural Equations Models (SEMs). Although very popular, these models have limited expressiveness and suffer from a variety of problems. This research program aims at overcoming some of the challenges involved in the formalization of actual causation. To this end, we will develop a comprehensive theory of actual causation that is based on a formal theory of action and change, and investigate its potential applications.
PI: Shakil M. Khan
Unmanned Aerial Vehicle Swarm Collaboration for Weed Control in Field Crops
This 16-month project was conducted with Precision.ai company in Saskatchewan. The main objective was to develop a multi-robot path planning system for weed control in field crops. The system relies on the collaboration between Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) to achieve two missions: weed mapping and weed spraying.
