Preprint Open access
EVOKE: Eliciting World Knowledge in Agents for Transferable Decision-Making
Large language models (LLMs) are increasingly deployed as agents for multi-step decision-making, yet transfer poorly to unseen environments. World-model methods address this by training agents to predict future observations, at the cost of additional training and errors that compound when predictions are used for plann …