Neuroscience-grounded memory for AI agents — ACT-R activation, Ebbinghaus forgetting, Hebbian learning, cognitive consolidation. Rust core + Python/TS legacy. Published on crates.io as engramai.

🧠 A tool for creating & running basic ACT-R models on multiple implementations using a single declarative file format

Predictive human performance modeling for UI/UX design

Mirror of the official ACT-R Lisp implementation

A Julia Package for the ACT-R Cognitive Architecture

Generate synthetic eye-tracking data using deep learning and ACT-R cognitive model

A set of tutorials for building likelihood based models in ACT-R

A Julia package for the ACT-R cognitive architecture

Source for ACT Rules website

A Python implementation of the ACT-R cognitive Architecture

A module to replace ACT-R's utility module with classic RL theory algorithms

Visual Studio Code proof of concept plugin for the ACT-R project http://act-r.psy.cmu.edu/

Cognitive architecture for emergent AI identity — blank slate to selfhood through lived experience

Brain-inspired persistent memory for AI coding assistants. MAGMA multi-graph, 3-stage retrieval, ACT-R + surprise scoring, constitutional governance, sleep consolidation, self-linking Zettelkasten. Successor to memory-v2.

A model of how reinforcement learning parameters affect performance on Raven's matrices

Cognitive memory substrate for AI agents that encodes selectively, consolidates autonomously, and shares context across sessions.

ACT-R Interactive Demo using Lemonade as a Case Study

Delayed Rule Inferral (Delayed vs Prepared control of motor responses)

🧠 一种基于联想记忆和 KAL 汇编指令集的认知引擎，将 LLM 限定为编解码器，知识与推理由符号系统完成

Brain-inspired persistent memory for AI coding assistants. Hybrid BM25+vector search, ACT-R activation scoring, FadeMem decay, knowledge graphs, multi-agent coordination. Successor to claude-memory.