Vehicle decision-making is analyzed and can be used to modify a decision-making process. For subsets of features comprising a vehicle operational scenario, a first value is generated that quantifies behavior of an artificial intelligence (AI) agent as the AI agent performs a sequence of actions within a first world model based on a complete set of observations for the subset of features. A first world model is a copy of a second world model for sequential decision making. A second value is generated that quantifies behavior of an AI agent as the AI agent performs a sequence of actions in the second world model based on an incomplete set of observations for the subset of features. A difference between the first and second values determines the impact of individual features on the AI agent within the second world model. A decision-making process of the AI agent can be updated.
Vehicle Decision Making Using Sequential Information Probing
31.07.2025
Patent
Elektronische Ressource
Englisch
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