In plain words: A network watches agents act in grid worlds and builds a model of each one's goals and beliefs, learning from many agents so it can read a new one quickly. It predicted random, rule-based, and trained agents and knew others can hold false beliefs.
Abstract
Theory of mind (ToM; Premack & Woodruff, 1978) broadly refers to humans' ability to represent the mental states of others, including their desires, beliefs, and intentions. We propose to train a machine to build such models too. We design a Theory of Mind neural network -- a ToMnet -- which uses meta-learning to build models of the agents it encounters, from observations of their behaviour alone. Through this process, it acquires a strong prior model for agents' behaviour, as well as the ability to bootstrap to richer predictions about agents' characteristics and mental states using only a small number of behavioural observations. We apply the ToMnet to agents behaving in simple gridworld environments, showing that it learns to model random, algorithmic, and deep reinforcement learning agents from varied populations, and that it passes classic ToM tasks such as the "Sally-Anne" test (Wimmer & Perner, 1983; Baron-Cohen et al., 1985) of recognising that others can hold false beliefs about the world. We argue that this system -- which autonomously learns how to model other agents in its world -- is an important step forward for developing multi-agent AI systems, for building intermediating technology for machine-human interaction, and for advancing the progress on interpretable AI.
Neil C. Rabinowitz, Frank Perbet, H. Francis Song, Chiyuan Zhang, S. M. Ali Eslami, Matthew Botvinick
arXiv:1802.07740 · cs.AI · submitted Feb 21, 2018 · updated Mar 12, 2018
abstract · pdf · html · 21 pages, 15 figures
It has been argued that people have an innate Theory of Mind. They use it to theorize about perhaps the most important thing we theorize about: other people.
So if someone drinks water, we surmise that they were thirsty (desire) and had the belief that drinking water would quench the thirst.
There is one big debate on whether people have a set of rules that they look up (unconsciously), or if they have a little "human simulator" where they throw in the action and out comes a belief/desire configuration. This is characterized as the debate between the "Theory Theory vs Simulation Theory").
Some theorists believe that autism is a disorder of this mechanism. Stated another way, some theorists believe that autists don't have a Theory of Mind. Consider this: in order to follow your gaze I would have to believe that you will look in a certain direction only if you are a person who would not want to look off in some random direction, and that you would look at something that is interesting or noteworthy.
https://en.wikipedia.org/wiki/Theory_of_mind
Anyway, if these scientists can produce a successful model that doesn't rely in explicit rules or a theory -- a neural net -- then others might look for evidence of this sort of computation in the brain. Alternatively, they could demonstrate that this model essentially encodes a set of rules, or perhaps they could collapse the debate into a hybrid theory.