  These days automation is being applied everywhere. In every environment,
planning for the actions to be taken by the agents is an important aspect. In
this paper, we plan to implement planning for multi-agents with a centralized
controller. We compare three approaches: random policy, Q-learning, and
Q-learning with Options Framework. We also show the effectiveness of planners
by showing performance comparison between Q-Learning with Planner and without
Planner.
