Clean baseline implementation of PPO using an episodic TransformerXL memory
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Updated
Jun 18, 2024 - Python
Clean baseline implementation of PPO using an episodic TransformerXL memory
A minimalist MVP demonstrating a simple yet profound insight: aligning AI memory with human episodic memory granularity. Shows how this single principle enables simple methods to rival complex memory frameworks for conversational tasks.
Code for paper "Episodic Memory Deep Q-Networks" (https://arxiv.org/abs/1805.07603), IJCAI 2018
Lu, Q., Hasson, U., & Norman, K. A. (2022). A neural network model of when to retrieve and encode episodic memories. eLife
PyTorch implementation of Episodic Meta Reinforcement Learning on variants of the "Two-Step" task. Reproduces the results found in three papers. Check the ReadMe for more details!
NaQ: Leveraging Narrations as Queries to Supervise Episodic Memory. CVPR 2023.
Psifr: Analysis and visualization of free recall data
Memory-centric architecture for scalable, energy-efficient AI agents and long-term cognition.
Memory that enables AI agents to persistently learn from past experiences, particularly failures, without requiring model weight updates, retraining, or fine-tuning.
Living Memory Dynamics - A novel framework for narrative-generating episodic memory with creative leaps. Features the Joshua R. Thomas Memory Equation.
A research-oriented Python framework implementing the DREAM architecture for long-term episodic memory in AI agents.
🧠 Proprietary Multimodal Cognitive Architecture - SpikingBrain + Long-VITA + Whisper with dynamic context, fusion layers, hybrid memory, and adaptive personality. Not a chatbot. A cognitive mind.
Pepper implementation of the cognitive architecture for Trust and Theory of Mind in humanoid robots applied to Vanderbilt's experiment.
Claude Codeプラグインマーケットプレイス。EpisodicRAG(階層的長期記憶)、EmailingEssay(AI駆動エッセイ配信)、VisualExpression(表情表現)の3プラグインを提供。
Local-first agent architecture separating episodic (events) and semantic (facts) memory, with provenance tracking, defense-in-depth LLM sanitization, and multilingual support via Qwen-2.5 + BGE-M3.
🧠 Build a cognitive architecture for AI that mimics human memory, separating episodic and semantic memory while ensuring multilingual support and data integrity.
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