Social Learning

Social learning investigates how agents acquire knowledge and adapt behaviors through interactions with others, mirroring human learning processes. Current research emphasizes developing algorithms and models, such as those based on multi-agent reinforcement learning, Bayesian and non-Bayesian approaches, and large language models (LLMs), to understand and replicate diverse social learning mechanisms, including imitation, cooperation, and information aggregation in various network structures. This field is significant for advancing artificial intelligence, particularly in creating more socially intelligent agents, and for providing insights into human behavior in complex social systems, including the spread of information and the formation of opinions.