Scientific Philosophy

Our research is guided by three fundamental scientific activities: Modeling, Measuring, and Solving. We view modeling as the foundation of scientific inquiry, measurement as the means of objective evaluation, and solving as the process of leveraging both to advance knowledge and solve real-world problems.

The asymmetry is intentional. We do not regard our scientific philosophy as complete. There may exist more fundamental principles or better ways to represent, organize, or extend it. Accordingly, we consider our scientific philosophy itself to be a subject of scientific inquiry.

Deep Decision Lab uses its scientific philosophy to classify its research contributions by Modeling, Measuring, and Solving.

Ongoing Research

Deep Learn Probablities for better Decisions Solving Modeling
Capable Agent Theory Modeling
Measuring conceptual framework generality, completeness, and orthogonality Measuring
Adaptive search over chromosome representations Solving Modeling Measuring

Archived Research

A Probabilistic Framework for Behavioral Identification from Animal-Borne Accelerometers (2022) Modeling Measuring Link
Supervised or Unsupervised Learning? Investigating the Role of Pattern Recognition Assumptions in the Success of Binary Predictive Prescriptions (2021) Measuring Modeling Link
Optimum Profit-Driven Churn Decision Making (2020) Solving Measuring Modeling Link
Does Extrinsic Motivation to Participate in Class Discussions Encourage Intrinsic Motivation for Learning? (2020) Measuring Link
Engineering Soft Skills vs. Engineering Entrepreneurial Skills (2019) Measuring Link
Cost-Driven Decision-Making Framework for Laser-Based Additive Manufacturing (2019) Solving Measuring Modeling Link
Quantifying Geometric Accuracy with Unsupervised Machine Learning (2018) Measuring Link
Optimum ANN-Based Breast Cancer Diagnosis (2018) Solving Measuring Modeling Link
Misfire and Valve Clearance Fault Detection in Combustion Engines (2018) Solving Modeling Link
Fluid Genetic Algorithm (FGA) (2017) Modeling Solving Link
SOED: Self-Organizing and Error-Driven Artificial Neural Network (2017) Modeling Solving Link
Distributed Decision Framework for Building Clusters (2016) Modeling Link
Improved Churn Prediction in the Telecommunication Industry (2014) Solving Link
Webpage Clustering – Taking the Zero Step (2014) Measuring Link
Hybrid GA–PSO for Multi-Period Inventory Routing (2013) Solving Link
Genetic Algorithm for Missing Value Estimation (2013) Solving Link

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