OUR CORE R&D / These systems range from individual

autonomous robotic platforms to large-scale, multi-agent systems

for information management, command & control

OUR CORE R&D

These systems range from individual  autonomous robotic platforms to large-scale, multi-agent systems  for information management, command & control

Probabilistic Programming

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Probabilistic Programming

By enhancing programming languages with probabilistic capabilities, we are able to create systems that can help make decisions in the face of uncertainty. Scientists and engineers at Charles River have been leaders in the field of probabilistic programming since its earliest days. Our current work includes developing probabilistic programming languages (PPLs) and applying PPLs to specific challenges, such as missile defense, space object classification, and the health of engineered systems.

Related Projects:

Scruff™

A framework for building artificial intelligence systems

STAPLES

Probabilistic programming solution for supply chain and logistics

Two US Army soldiers looking at computer monitors showing images of robotic combat vehicles.

RAPS

A maintenance system that can predict the health and status of robotic combat vehicles

POWERED

A predictive health and maintenance app for critical energy equipment

PSI-Coach

A socially intelligent AI coach for predicting and maximizing team performance

chess

COLTRANE

A system that helps AI systems navigate novel situations

PLEDGES

A new machine learning approach with probabilistic modeling

PRESCRIPTION

A system for understanding risks and vulnerabilities in the pharmaceutical supply chain

PROBSYSML

Probabilistic extensions for the Systems Modeling Language

SNAPPR

Probabilistic Reasoning for System Components Onboard US Naval Vessels

TAMBA

TAMBA

Technology to evaluate the effectiveness of privacy-aware systems

APPRIL

A probabilistic programming language to simplify machine learning

FIGARO

An open-source probabilistic programming language

MAAGI

Software to detect and analyze malware attacks