Definition
Saving the full state of an AI agent's environment so it can rewind if it makes a mistake.
The operation of capturing combined filesystem and process-memory state of a running sandbox atomically, supporting later rollback to that exact state for tree-search agents and RL training.
Also called: sandbox checkpointing