Human Like Strategy

Research on human-like strategies in artificial intelligence focuses on developing AI agents that can effectively interact with and cooperate with humans in various complex scenarios, such as negotiations, games, and robotic tasks. Current approaches leverage machine learning techniques, including reinforcement learning and neural networks (like LSTMs and MDNs), often incorporating elements of game theory and natural language processing to model and replicate human decision-making processes. This research is significant because it addresses the limitations of traditional AI approaches that struggle with the nuances of human interaction, paving the way for more effective and collaborative human-AI partnerships in diverse applications.