{"id":15,"date":"2011-04-17T12:10:30","date_gmt":"2011-04-17T12:10:30","guid":{"rendered":"http:\/\/www.ai.rug.nl\/SocialCognition\/?page_id=15"},"modified":"2017-02-22T14:25:03","modified_gmt":"2017-02-22T14:25:03","slug":"experiments","status":"publish","type":"page","link":"https:\/\/www.ai.rug.nl\/SocialCognition\/experiments\/","title":{"rendered":"Experiments"},"content":{"rendered":"

Teaching children \u00a0to attribute second-order false beliefs: A training study<\/span><\/strong><\/p>\n

<\/span><\/strong>We designed a new experiment in which we trained children of ages 5 and 7 with second-order false belief stories to investigate which kind of feedback (if any) will help them. Second-order false belief stories are stories in which the children are asked to attribute a second-order belief such as \u201cMarja thinks that Ken thinks that she took potatoes\u201d, where the children know that Marja\u2019s belief is in fact false. For this purpose, we constructed 34 stories with related pictures. All of the pictures have been designed by the professional artist Avik Kumar Maitra. This link<\/a> shows one of the stories and the related pictures.<\/p>\n

Modeling developmental transitions in reasoning about false beliefs of others<\/strong><\/span><\/p>\n

We constructed an ACT-R model in order to show the developmental transitions in reasoning about false beliefs of others. These stand for a child\u2019s reasoning from his\/her own point of view (zero-order) to taking into consideration an other agent\u2019s beliefs (first-order) and later to taking into consideration an other agent\u2019s beliefs about other agents\u2019 beliefs (second-order). You can find the model\u00a0code\u00a0here<\/a>.<\/p>\n

Marble Drop game to investigate adults’ second-order theory of mind<\/span><\/strong><\/p>\n

One paradigm that we currently use to investigate higher-order social cognition is the Marble Drop game. You can read about it here<\/a>.<\/p>\n

Using computer agents to discover the benefit of higher-order theory of mind reasoning<\/strong><\/span><\/p>\n

It is difficult to control how much theory of mind a human participant can use in an experimental setting. This makes it hard to experimentally determine the effectiveness of higher-order theory of mind reasoning across different settings. Instead, we can make use of computational agents that are designed to differ in their theory of mind abilities. Simulations using these agents show that the use of higher-order theory of mind can be beneficial to agents. To show how this benefit works, there are a number of applets and scripts on this site that simulate interactions between computer agents in different settings. These applets show how higher-order theory of mind can benefit agents in competitive settings such as rock-paper-scissors<\/a> or Limited Bidding<\/a>. But agents can also benefit from the use of higher-order theory of mind in a more cooperative settings such as the Tacit Communication Game<\/a>. However, it turns out that higher-order order theory of mind plays an important role in mixed-motive settings, where cooperative and competitive aspects both play a role. An example of such a mixed-motive setting is negotiation in Colored Trails, both in single-shot negotiation<\/a> settings and multi-round negotiation<\/a> settings.<\/p>\n

In negotiation settings, theory of mind can benefit agents as well. In an online appendix to the paper “Higher-order theory of mind in negotiations under incomplete information”, we show the mathematical details of how theory of mind agents function in the game of Colored Trails. This appendix can be downloaded here<\/a>.<\/p>\n

Evolution of altruistic punishment in heterogeneous populations<\/strong><\/span><\/p>\n

Evolutionary models of cooperation generally assume that groups consist of homogeneous individuals. In these models, each individual experiences the same risk associated with cooperation, has the same benefits from successful cooperation, and is equally capable of punishing those that fail to cooperate. This applet<\/a> shows how heterogeneity among individuals can affect cooperative behavior in a public goods game.<\/p>\n

MSc Projects<\/strong><\/h2>\n

Where does Jack think that Mary will look for the chocolate? <\/strong>Investigating the reasoning steps while answering questions about other agents, in an <\/strong>eye-tracking study<\/strong><\/p>\n

Supervision:\u00a0Rineke Verbrugge, e-mail\u00a0L.C.Verbrugge@rug.nl<\/a><\/p>\n

Burcu Arslan, e-mail\u00a0b.arslan@rug.nl<\/a><\/p>\n

Adults are good at reasoning about an agent who is reasoning about another agent (e.g. \u201cJohn thinks<\/em> that Mary thinks<\/em> that there is an apple on the table\u201d). However, we do not know the steps of the process of reasoning that adults go through (see Arslan, Taatgen, & Verbrugge, 2013 for a computational model that predicts children\u2019s reasoning steps).<\/p>\n

We constructed 30 different Dutch stories to test participants\u2019 reasoning abilities about other agents\u2019 mental states. In the planned project, adult participants will listen to these stories with the help of headphones and watch the related drawings on the computer. They will be expected to answer a few questions about each of the stories (see Arslan, Verbrugge, Taatgen, & Hollebrandse for a study with children).<\/p>\n

In this project, you will investigate adults\u2019 eye-movements while they are answering questions in which they are supposed to reason about other agents\u2019 mental states. You are expected to write a MATLAB code to run the experiment, to find 25 participants between the ages 18 and 35 to conduct the experiment, to analyse the eye-tracking data, and to write a report.<\/p>\n

References<\/p>\n

Arslan, B., Taatgen, N. A., & Verbrugge, R. (2013). Modeling Developmental \u00a0\u00a0\u00a0 Transitions in Reasoning about False Beliefs of Others. In R. West & T. Stewart (eds.), Proceedings of the 12th International Conference on Cognitive Modeling<\/em>, Ottawa:Carleton University. 77-82. (http:\/\/www.ai.rug.nl\/~barslan\/resources\/Arslan_Taatgen_Verbrugge_2013.pdf)<\/p>\n

Arslan, B., Verbrugge, R., Taatgen, N. & Hollebrandse, B. (2014). Teaching children to attribute second-order false belief: A training study. In Szymanik, J. & Verbrugge, R. (eds.), Proceedings of the Second Workshop Reasoning About Other Minds: Logical and Cognitive Perspectives, co- located with Advances in Modal<\/em> Logic,<\/em> Groningen, The Netherlands, 1208, pp. 1-5.(http:\/\/www.ai.rug.nl\/~barslan\/resources\/Arslan_et_al._2014.pdf)<\/p>\n

Modeling strategies for turn-based games<\/strong><\/p>\n

Supervision:\u00a0Rineke Verbrugge, e-mail\u00a0L.C.Verbrugge@rug.nl<\/a><\/p>\n

Stedan Wierda, e-mail\u00a0Wierda.stefan@gmail.com<\/a><\/p>\n

Theory of mind, the ability to reason about other people\u2019s knowledge and plans, can be studied using a wide range of tasks. One of these tasks, namely playing strategic games, has been utilized quite frequently in these studies. A marble drop game (cf. Figure 1) \u2014 a two-player turn-based game developed at our AI institute in Groningen \u2014 is one such.<\/p>\n

Recently, we modeled two possible strategies for players in this game in ACT-R and ACTransfer (an extension of ACT-R). However, you can imagine that a large variety of strategies are possible for players involved in a game like marble drop. We have formulated a list of possible strategies that could be used to play the game, taking into account some of the constraints of the human mind. The goal of this project is to implement the formalized strategies into ACT-R models. Consequently, the reaction times predicted by the models will be tested against existing experimental results from previous studies performed at our institute. This will aid in the investigations of the usage of formal methods in cognitive studies.\u00a0 For this project, some experience with the ACT-R cognitive architecture is required and coding skills form a pre-requisite.<\/p>\n

References<\/p>\n

B. Meijering, H. van Rijn, N.A. Taatgen and R. Verbrugge, What eye movements can tell about theory of mind in a strategic game. PLoS ONE<\/em>, 7<\/strong> (9) (2012), e45961. http:\/\/www.plosone.org\/article\/info%3Adoi%2F10.1371%2Fjournal.pone.0045961<\/p>\n

S. Ghosh, B. Meijering and R. Verbrugge, Strategic reasoning: Building cognitive models from logical formulas. Journal of Logic, Language and Information<\/em>, 23<\/em>(1) (2014) 1-29. http:\/\/link.springer.com\/article\/10.1007\/s10849-014-9196-x#page-1<\/p>\n

Bachelor Projects<\/strong><\/h2>\n

Where does Jack think that Mary will look for the chocolate? Investigating the reasoning steps while answering questions about other agents in an eye-tracking study<\/strong><\/p>\n

Adults are good at reasoning about an agent who is reasoning about another agent (e.g. \u201cJohn thinks that Mary thinks that there is an apple on the table\u201d). However, we do not know the steps of the process of reasoning that adults go through (see Arslan, Taatgen, & Verbrugge, 2013 for a computational model that predicts children\u2019s reasoning steps).<\/p>\n

We constructed 30 different Dutch stories to test participants\u2019 reasoning abilities about other agents\u2019 mental states. In the planned project, adult participants will listen to these stories with the help of headphones and watch the related drawings on the computer. They will be expected to answer a few questions about each of the stories (see Arslan, Verbrugge, Taatgen, & Hollebrandse for a study with children). <\/p>\n

In this project, you will investigate adults\u2019 eye-movements while they are answering questions in which they are supposed to reason about other agents\u2019 mental states. You are expected to test 10 participants between the ages 18 and 35 to conduct the experiment, to analyse the eye-tracking data, and to write a report.<\/p>\n

Supervision: Rineke Verbrugge, e-mail L.C.Verbrugge@rug.nl<\/a> and Burcu Arslan, e-mail b.arslan@rug.nl<\/a><\/p>\n

References<\/p>\n