Search Results for "learning classifier system"

turbovec is a Rust-based vector index with Python bindings for fast similarity search. It is built around TurboQuant, a quantization approach designed to reduce vector storage while preserving useful distance information. The project targets workloads where embedding search needs to be compact, efficient, and practical to integrate into Python applications. It avoids a separate training phase for the quantizer, which can simplify setup compared with systems that require codebook learning....

ENAS in PyTorch is a PyTorch implementation of Efficient Neural Architecture Search (ENAS), a method that automates the design of neural network architectures through reinforcement learning and parameter sharing. The repository demonstrates how a controller network can explore a large search space and discover high-performing architectures while dramatically reducing the computational cost traditionally associated with neural architecture search. It is primarily intended as a research and...

It is a desktop search (aiming learning materials) tool that provides full text search with a friendly GUI

Didaskon will deliver a framework for assembling a curriculum from existing learning objects provided by e-Learning services. The selection of learning objects will be based on the semantically annotated specification of the user's current skills.

PALOMA Suite allows the referencing of learning resources using metadata according to the international IEEE LOM standard, and SCORM, CANCORE and Normetic application profiles. PALOMA Suite contains: PALOMA (Standard), PALOMAWeb and PALOMARepository.

The project is building an E-Learning Framework (ELF - JISC) toolkit based around an eProfile server (ELF Producer) that will maintain individuals personal profiles and will support the social networks and relationships that exist between these users.

ScenConnect shows scenarios as networks of situation and event tag sets, for fast comparisons. It links scenarios to tags, scores, and other metadata, creating situationals suitable for search, mining, machine learning, and planning.