LIRa Session: Rineke Verbrugge

Speaker: Rineke Verbrugge (University of Groningen)

Date and Time: Thursday, May 12th 2022, 16:30-18:00, Amsterdam time.

Venue: online.

Title: Effectiveness of higher-order theory of mind in competitive, cooperative and mixed-motive situations

Abstract. When engaging in intelligent interaction, people rely on their ability to reason about other people’s mental states, including goals, intentions, and beliefs. This theory of mind ability allows them to more easily understand, predict, and manipulate the behavior of others. People can use their theory of mind recursively, which allows them to understand second-order attributions such as “Alice believes that Bob does not know that she wrote a novel under pseudonym”. This ability is unique to humans: animals may or may not exhibit some forms of first-order theory of mind, but definitely no higher orders.

Using agent-based modeling, Harmen de Weerd, Bart Verheij and I have shown that higher-order theory of mind reasoning can be useful across competitive, cooperative, and mixed-motive settings. In this lecture, we discuss these results and we cast a new light on mixed-motive situations by investigating how the predictability of the environment influences the effectiveness of higher-order theory of mind. Our results show that the benefit of higher-order theory of mind reasoning depends on the predictability of the environment. We consider agent-based simulations in repeated one-shot negotiations in the negotiation game ‘Colored Trails’. When this environment is highly predictable, agents obtain little benefit from theory of mind reasoning. However, if the environment has more observable features that change over time, agents without the ability to use theory of mind experience more difficulties predicting the behavior of others accurately. This in turn allows theory of mind agents to obtain higher scores in these more dynamic environments. These results suggest that the human-specific ability for higher-order theory of mind reasoning may have evolved to allow us to survive in more complex and unpredictable environments.