The document proposes an adaptive opportunistic routing scheme for wireless ad-hoc networks. It uses a reinforcement learning framework to route packets opportunistically even without reliable knowledge of channel statistics or network model. This distributed approach allows each node to make routing decisions based on local information to optimally explore and exploit opportunities in the network. The implementation involves planning, investigating existing systems, designing a changeover method, and evaluating the changeover. It uses a d-Adaptor algorithm and modules for initialization, transmission, acknowledgement message passing, and relays.