Selfish Agent

Selfish agents, computational entities prioritizing individual gain over collective benefit, are a central focus in multi-agent systems research. Current research investigates how to design and control such agents, often employing reinforcement learning and federated learning frameworks, to achieve socially desirable outcomes despite their inherent selfishness. This research is crucial for addressing challenges in diverse fields like energy management, resource allocation, and human-AI interaction, where the interplay between individual and collective goals necessitates careful design of agent architectures and incentive mechanisms. The ultimate goal is to develop methods for aligning selfish agent behavior with broader societal objectives, improving efficiency and fairness in complex systems.