Probabilistic models are integral to state-of-the-art decision theories, such as Bayesian a.k.a. evidential, quantum-like Bayesian, causal, and functional/updateless/timeless decision theories. To enable widespread and inclusive adoption of these decision theories by businesses and in public service, there is a pressing need for an open-source decision intelligence stack. This stack should span from sensing (data collection) and actuation to online learning and natural-language decision assistance.
The Open-Source Stack for Decision Intelligence
The Open-Source Stack for Decision…
The Open-Source Stack for Decision Intelligence
Probabilistic models are integral to state-of-the-art decision theories, such as Bayesian a.k.a. evidential, quantum-like Bayesian, causal, and functional/updateless/timeless decision theories. To enable widespread and inclusive adoption of these decision theories by businesses and in public service, there is a pressing need for an open-source decision intelligence stack. This stack should span from sensing (data collection) and actuation to online learning and natural-language decision assistance.