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 26 of 99
2020
Dynamic Programming for Predict+ Optimise.
E Demirovic, PJ Stuckey, T Guns, J Bailey, C Leckie, K Ramamohanarao, ...
Proceedings of the AAAI Conference on Artificial Intelligence 34 (02), 1444-1451, 2020
Research38 citationsVariational autoencoders for sparse and overdispersed discrete data
H Zhao, P Rai, L Du, W Buntine, D Phung, M Zhou
International conference on artificial intelligence and statistics, 1684-1694, 2020
Research30 citationsEuclidean pathfinding with compressed path databases
B Shen, MA Cheema, DD Harabor, PJ Stuckey
International Joint Conference on Artificial Intelligence-Pacific Rim …, 2020
Research23 citationsCore-guided and core-boosted search for CP
G Gange, J Berg, E Demirović, PJ Stuckey
International Conference on Integration of Constraint Programming …, 2020
Optimization21 citationsExact approaches to the multi-agent collective construction problem
E Lam, PJ Stuckey, S Koenig, TKS Kumar
International Conference on Principles and Practice of Constraint …, 2020
Multi-Agent Systems21 citationsBayesian network classifiers using ensembles and smoothing
H Zhang, F Petitjean, W Buntine
Knowledge and Information Systems 62 (9), 3457-3480, 2020
Bayesian Methods21 citationsTowards accurate predictions and causal ‘what-if’analyses for planning and policy-making: A case study in emergency medical services demand
K Bandara, C Bergmeir, S Campbell, D Scott, D Lubman
Forecasting18 citationsNutmeg: a MIP and CP hybrid solver using branch-and-check
E Lam, G Gange, PJ Stuckey, P Van Hentenryck, JJ Dekker
SN Operations Research Forum 1 (3), 22, 2020
Research18 citationsSolving satisfaction problems using large-neighbourhood search
G Björdal, P Flener, J Pearson, PJ Stuckey, G Tack
International Conference on Principles and Practice of Constraint …, 2020
Optimization18 citationsMachine learning after the deep learning revolution
W Buntine
Frontiers of Computer Science 14 (6), 146320, 2020
Machine Learning17 citationsOptimal decision lists using SAT
J Yu, A Ignatiev, PL Bodic, PJ Stuckey
arXiv preprint arXiv:2010.09919, 2020
Research16 citationsOnline computation of euclidean shortest paths in two dimensions
R Hechenberger, PJ Stuckey, D Harabor, P Le Bodic, MA Cheema
Proceedings of the International Conference on Automated Planning and …, 2020
Research16 citations
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