Machine Theory of Mind

In this episode of The Turing Talks, we introduce the innovative Theory of Mind neural network (ToMnet), which utilizes meta-learning to model agents by analyzing their behavior. The ToMnet is designed with three key modules: a character net that processes past actions, a mental state net for current behavioral analysis, and a prediction net for forecasting future actions. We discuss various experiments demonstrating how the ToMnet approximates optimal inference, infers goals, and recognizes agents' false beliefs. This framework not only advances multi-agent AI systems but also holds potential for improving machine-human interactions and fostering interpretable AI.