Research & Decision Science
Research built into the product
Forecasting, optimization and applied AI for real decisions under real constraints.
- indexed research outputs
- 1,181indexed research outputs
- combined citations
- 53,485combined citations
- Clarivate Highly Cited Papers in forecasting
- Top 1%Clarivate Highly Cited Papers in forecasting
Scientific foundations
From research result to product behavior
Probabilistic forecasts, coherent hierarchies, constraint-aware recommendations and governed human intervention.
Research → product
| Research area | Enterprise problem | RabbitHawk capability |
|---|---|---|
| Hierarchical forecasting | Local forecasts do not aggregate coherently across the enterprise | Reconciled forecasts across every level |
| Probabilistic forecasting | Point forecasts hide risk | Full predictive distributions, intervals and scenario ranges |
| Optimization | Forecasts do not tell teams what to do | Constraint-aware recommendations |
| Agentic AI | Context is trapped in emails and notes | Adaptive elicitation, semantic routing and governed context workflows |
| Human-in-the-loop AI | Automation without trust creates resistance | Belief review, governed publication and intervention lineage |
| Alignment science | Teams optimize against conflicting goals | Goals & Guardrails within Forecasting & Optimization |
Hierarchical forecasting
Local forecasts do not aggregate coherently across the enterprise
Reconciled forecasts across every level
Probabilistic forecasting
Point forecasts hide risk
Full predictive distributions, intervals and scenario ranges
Optimization
Forecasts do not tell teams what to do
Constraint-aware recommendations
Agentic AI
Context is trapped in emails and notes
Adaptive elicitation, semantic routing and governed context workflows
Human-in-the-loop AI
Automation without trust creates resistance
Belief review, governed publication and intervention lineage
Alignment science
Teams optimize against conflicting goals
Goals & Guardrails within Forecasting & Optimization
Research database
Search the indexed record by title, author, venue, category or year. Records include peer-reviewed work, preprints, books, chapters and other scholarly outputs.
1,181 results · page 55 of 99
2013
Structure based extended resolution for constraint programming
G Chu, PJ Stuckey
arXiv preprint arXiv:1306.4418, 2013
Machine Learning5 citationsInductive definitions in constraint programming
RA Aziz, PJ Stuckey, Z Somogyi
Proceedings of the Thirty-Sixth Australasian Computer Science Conference …, 2013
Machine Learning5 citationsStatistical inference of protein" LEGO bricks"
AS Konagurthu, L Allison, D Abramson, PJ Stuckey, AM Lesk
Bayesian Methods4 citationsFinite type extensions in Constraint Programming (extended version)
R Caballero, PJ Stuckey, A Tenorio-Fornés
Technical Report SIC-05/13, Facultad de Informática, Universidad Complutense …, 2013
Machine Learning4 citationsNew approaches in time series forecasting: methods, software and evaluation procedures
CN Bergmeir
Universidad de Granada, 2013
Forecasting3 citationsThose who cannot remember the past are condemned to repeat it
PJ Stuckey
International Conference on Principles and Practice of Constraint …, 2013
Research3 citationsFinite type extensions in constraint programming
R Caballero, PJ Stuckey, A Tenorio-Fornés
Proceedings of the 15th Symposium on Principles and Practice of Declarative …, 2013
Machine Learning3 citationsUnsatisfiable cores for constraint programming
N Downing, T Feydy, PJ Stuckey
arXiv preprint arXiv:1305.1690, 2013
Machine Learning2 citationsRsiopred: An R package for forecasting by exponential smoothing with model selection by a fuzzy multicriteria approach
C Bergmeir, JM Benítez, J Bermúdez, JV Segura, E Vercher
The R User Conference, useR! 2013 July 10-12 2013 University of Castilla-La …, 2013
ForecastingStatistical Inference of a canonical dictionary of protein substructural fragments
AS Konagurthu, AM Lesk, D Abramson, PJ Stuckey, L Allison
arXiv preprint arXiv:1310.1462, 2013
Bayesian Methods- Machine Learning
Automated Design of Search with Composability.
A Sabharwal, H Samulowitz, T Schrijvers, PJ Stuckey, G Tack
AAAI (Late-Breaking Developments), 2013
Optimization
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