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Found 6 papers, 1 papers with code
Bottom-Up Grounding in the Probabilistic Logic Programming System Fusemate
This paper introduces the Fusemate probabilistic logic programming system.
Movement Analytics: Current Status, Application to Manufacturing, and Future Prospects from an AI Perspective
From an application perspective, we review applications of these methods to movement analytics in a general sense and across various industries.
North Carolina COVID-19 Agent-Based Model Framework for Hospitalization Forecasting Overview, Design Concepts, and Details Protocol
This Overview, Design Concepts, and Details Protocol (ODD) provides a detailed description of an agent-based model (ABM) that was developed to simulate hospitalizations during the COVID-19 pandemic.
SMART: An Open Source Data Labeling Platform for Supervised Learning
SMART is an open source web application designed to help data scientists and research teams efficiently build labeled training data sets for supervised machine learning tasks.
Tableaux for Policy Synthesis for MDPs with PCTL* Constraints
Policy synthesis addresses the problem of how to control or limit the decisions an agent makes so that a given specification is met.
Blocking and Other Enhancements for Bottom-Up Model Generation Methods
Overall, the results showed bottom-up model generation methods were good for disproving theorems and generating models for satisfiable problems, but less efficient than SPASS in auto mode for unsatisfiable problems.
