The RAMP strategy integrates deep reinforcement learning with online action model learning to automate planning in numeric domains. It replaces the need for offline expert traces by refining models through direct environment interaction. This feedback loop allows the system to plan future actions autonomously. Practitioners gain a method for deploying agents in complex, data-scarce numeric environments.