Multi-agent systems (MAS) are a branch of artificial intelligence that focuses on the study of systems in which multiple agents interact with each other to achieve individual and collective goals. Each agent in the system is autonomous, meaning it can make decisions and take actions independently, based on its own goals and knowledge. MAS research addresses a wide range of applications, from simple online shopping websites with multiple sellers and buyers to complex systems in areas such as logistics, network routing, and social networks. The main goals of MAS research are to understand how agents can work together effectively, coordinate their actions, and adapt to changing environments. Some key challenges in MAS research include determining how agents can communicate and share information with each other, how they can reach agreements and make decisions collectively, and how they can adapt their behavior in response to changes in their environment or in the behavior of other agents. MAS research draws upon concepts from game theory, economics, sociology, and computer science to address these challenges and develop practical solutions for building robust and efficient multi-agent systems.