think-probabilistic

What problem does it solve?

Handles uncertainty in reasoning by offering structured probabilistic methods (Bayesian updating and Evidential reasoning) to update beliefs and fuse multi-source evidence.

Core Features & Use Cases

• Bayesian inference for updating prior beliefs with new data and computing posteriors across sequential evidence.
• Evidential reasoning (Dempster-Shafer) to combine evidence from multiple sources and express ignorance and conflict.
• Use cases include risk assessment, decision support under uncertainty, hypothesis evaluation, and multi-source evidence synthesis.

Quick Start

Provide a hypothesis and a stream of evidence, and I will compute a posterior probability using Bayesian updating or Dempster–Shafer reasoning.