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 48 of 99
2015
Package ‘rsnns’
C Bergmeir, JM Benítez
Research3 citations- Research3 citations
Research on domain-oriented latent policy lineage mining method
G Liu, W Buntine, X Yang, W Fu
2015 eighth international conference on internet computing for science and …, 2015
Machine Learning2 citationsAutomatic minimal-height table layout
M Bilauca, G Gange, P Healy, K Marriott, P Moulder, PJ Stuckey
INFORMS Journal on Computing 27 (3), 449-461, 2015
Research1 citationsOptimisation and Relaxation for Multiagent Planning in the Situation Calculus
TO Davies, AR Pearce, PJ Stuckey, H Søndergaard
Proceedings of the 2015 International Conference on Autonomous Agents and …, 2015
Optimization1 citationsMaking Topic Models More Usable
W Buntine
Proceedings of the 2015 Workshop on Topic Models: Post-Processing and …, 2015
Research1 citationsDynamic capacity control and balancing in the medium voltage grid (doctoral consortium)
F De Nijs, MTJ Spaan, MM De Weerdt
AAMAS 2015: 14th International Conference on Autonomous Agents and …, 2015
ResearchTwo type extensions for the constraint modelling language MiniZinc
R Caballero Roldán, PJ Stuckey, Á Tenorio Fornés
Elsevier, 2015
Machine LearningUnsatisfiable Cores and Lower Bounding for Constraint Programming
N Downing, T Feydy, PJ Stuckey
arXiv preprint arXiv:1508.06096, 2015
Machine LearningPart I The Resource-Constrained Project Scheduling Problem 1 Shifts, Types, and Generation Schemes for Project Schedules......
R Kolisch, C Artigues, O Koné, P Lopez, M Mongeau, S Knust, A Agarwal, ...
Handbook on Project Management and Scheduling Vol. 2, 626, 2015
Machine LearningТом. 5. Proceedings of the 29th AAAI Conference on Artificial Intelligence, AAAI 2015 and the 27th Innovative Applications of Artificial Intelligence Conference, IAAI 2015.-Сер …
RA Aziz, G Chu, C Muise, P Stuckey, T Keller, F Geißer, A Ramdas, ...
Machine LearningConstraint Programming approach to the Steiner tree problem with side constraints using learning
D de Una, G Gange, P Schachte, PJ Stuckey
Machine Learning
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