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

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.

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.

Local graph-based memory for agents. Memories reinforce when used and fade when ignored.

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.

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