We would first integrate navigation and perception code with manipulation code to enhance our robotic system's automacy. After this, we would design collaborative strategies that allow the robot to operate in a multi-agent environment. For the strategies, the robot needs to observe the number of blocks for each color, ensuring that when building our pattern, we use at most half of the blocks available for each color. This precaution ensures that there are enough resources available for the other robot, maintaining a balanced and fair resource allocation. To refine our strategy, we plan to design a Resource Allocation Game using Game Theory approaches. This will be complemented by Predictive Modeling, which leverages previous data from playing games using the learned approach. Furthermore, we aim to add a second robot in the simulation to implement and test the collaborative strategies effectively. Finally, we will incorporate the SLAM (Simultaneous Localization and Mapping) algorithm to improve the localization of various blocks, enhancing the overall efficiency and coordination of our robotic systems.