Tag
Proposes a reinforcement learning framework that uses locally linear embeddings to capture environment dynamics and an attention mechanism to adaptively fuse dynamics-specific and reward-specific features, inspired by neural principles, improving learning efficiency.
The article describes Skynet, an Elixir-based framework using OTP GenServers to build persistent cognitive architectures for LLM agents. It implements a layered memory stack inspired by neuroscience, addressing the amnesia problem in long-running agents.
Microsoft researchers propose a biologically-inspired memory architecture for LLM agents that incorporates mechanisms like sleep-phase consolidation and interference-based forgetting to manage persistent memory efficiently.
The paper introduces Mela, a memory-augmented transformer architecture inspired by human memory consolidation, featuring a Hierarchical Memory Module that improves long-context language modeling performance.