In general, RL-based reasoning methods strive to find relational paths to tune their reasoning policies for predictions and formulate the path-finding problem as a Markov decision process (MDP).
in such a process, the policy-based agent decides to take an action a ∈ A from the current state (i.e., the current entity and its context information) s ∈ S to reach the next one according to its reasoning policy π, where the action space is defined as all the relations in G. each relational chain in the relational paths can be considered as a reasoning chain.