Records found: 4
'Meta's DreamGym synthesizes environment interactions as text using a reasoning experience model and grounded replay memory, cutting real rollouts and boosting RL performance across web benchmarks.'
A PyTorch tutorial demonstrating how to build a memory-augmented agent that uses differentiable memory, prioritized experience replay and meta-learning to adapt continuously without catastrophic forgetting.
'A hands-on tutorial showing how to build an Advanced Neural Agent with stability-first engineering: Xavier init, clipping, adaptive LR, momentum, and experience replay. Includes full Python code and demo utilities for regression and RL-style tasks.'
LifelongAgentBench introduces a novel benchmark for evaluating continuous learning in LLM-based agents, focusing on knowledge retention and adaptation across sequential tasks in dynamic environments.