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Found 5 papers, 0 papers with code
RECAP-KG: Mining Knowledge Graphs from Raw GP Notes for Remote COVID-19 Assessment in Primary Care
By relying on support phrases mined from the SNOMED ontology, as well as predefined supported facts from values used in the RECAP (REmote COVID-19 Assessment in Primary Care) patient risk prediction tool, our graph generative framework is able to extract structured knowledge graphs from the highly unstructured and inconsistent format that consultation notes are written in.
Combining Experts' Causal Judgments
We formally define the notion of an effective intervention, and then consider how experts' causal judgments can be combined in order to determine the most effective intervention.
Learning Neural Search Policies for Classical Planning
In this paper, we introduce a parametrized search algorithm template which combines various search techniques within a single routine.
Learning Classical Planning Strategies with Policy Gradient
This enables using policy gradient to learn search strategies tailored to a specific distributions of planning problems and a selected performance metric, e. g. the IPC score.
Towards learning domain-independent planning heuristics
Automated planning remains one of the most general paradigms in Artificial Intelligence, providing means of solving problems coming from a wide variety of domains.
