and then a sequential Colonel Blotto game model is constructed. An optimal dismantling method for combat networks is proposed with graph embedding representation reinforcement learning aided policy ...

The relative motion diagram is shown as Figure 1 and ... to obtain reasonable maneuver strategies in complex game confrontation scenarios through deep reinforcement learning, which can solve the ...

Using as many line return data as possible as samples, the deep Q-network (DQN), a deep reinforcement learning algorithm, is used to obtain the Nash equilibrium of the game model ... Interlocking ...

and sharing data for sequential decision making, including offline reinforcement learning, learning from demonstrations, and imitation learning. RLDS makes it simple to share datasets without losing ...