MIT Schwarzman College of Computing

Researchers from MIT and the University of Washington have developed a model to predict the behavior of human and artificial intelligence (AI) agents, taking into account computational constraints. The model automatically deduces these constraints by processing previous actions of the agent. This "inference budget" can help predict future behavior of the agent; for instance, it…

Researchers at the Massachusetts Institute of Technology (MIT) and the University of Washington have developed a model that accounts for the computational constraints often experienced by decision-making agents, both human and machine. This model auto-infers an agent's computational restrictions by analysing traces of past actions, which, in turn, can be used to predict future behaviour. In…

MIT and University of Washington researchers have created a model to efficiently predict human behavior, which could potentially improve the effectiveness of AI systems working with human collaborators. Humans tend to behave suboptimally when making decisions due to computational constraints and researchers have created this model to account for these human processing limitations. The model…

Scientists from the Massachusetts Institute of Technology (MIT) and the University of Washington have developed an approach to mechanically infer the computational weaknesses of an AI or human agent by observing prior activities. This perceptible agent’s "inference budget" can be used to predict future behavior. Used in forthcoming AI structures, the technique could allow them…

Researchers at MIT and the University of Washington have developed a method to effectively model human behavior, accounting for the computational constraints that limit our decision-making abilities. This model, known as the "inference budget," enables predictions of an individual’s future actions based on their past behaviors. This is particularly useful in AI development, allowing machines…