A Language for Modeling Cultural Norms, Biases and Stereotypes for Human Behavior Models

Solomon, Steven Davidoff; Lent, Michael van; Core, Mark G.; Carpenter, Paul B.; Rosenberg, Milton

doi:10.21236/ada480481

Cited by 16 publications

(10 citation statements)

References 18 publications

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“…For instance, the CAB model [48] allows the explicit encoding of specific cultural norms and stereotypes in a task-oriented model. Furthermore, Thespian [47], an agent architecture based on the PsychSim framework [42], focuses on representing social obligations during conversations.…”

Section: Related Workmentioning

confidence: 99%

“…Both agents will also initialize their mental model of the user, B User , in a similar manner. This is a crude initialization process that can be refined in the future, for instance, through the use of stereotypes as it is done in the CAB model [48].…”

Section: Impact On Belief Revisionmentioning

confidence: 99%

“…With a few exceptions [34], most cognitive agent models of culture have focused on specific norms [47,48] or on exploring how culture affects instrumental decisions, such as in negotiation tasks [16,39]. Instead, the work described here focuses on representing cognitive biases in judging the appropriateness of social actions in everyday social interaction.…”

Section: Introductionmentioning

confidence: 99%

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Modeling culture in intelligent virtual agents

Mascarenhas

Degens

Paiva

et al. 2015

Auton Agent Multi-Agent Syst

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This work addresses the challenge of creating virtual agents that are able to portray culturally appropriate behavior when interacting with other agents or humans. Because culture influences how people perceive their social reality it is important to have agent models that explicitly consider social elements, such as existing relational factors. We addressed this necessity by integrating culture into a novel model for simulating human social behavior. With this model, we operationalized a particular dimension of culture-individualism versus collectivism-within the context of an interactive narrative scenario that is part of an agent-based tool for intercultural training. Using this scenario we conducted a cross-cultural study in which participants from a collectivistic country (Portugal) were compared with participants from an individualistic country (the Netherlands) in the way they perceived and Multi-Agent Syst (2016) 30:931-962 interacted with agents whose behavior was either individualistic or collectivistic, according to the configuration of the proposed model. In the obtained results, Portuguese subjects rated the collectivistic agents more positively than the Dutch but both countries had a similarly positive opinion about the individualistic agents. This experiment sheds new light on how people from different countries differ when assessing the social appropriateness of virtual agents, while also raising new research questions on this matter.

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Section: Related Workmentioning

confidence: 99%

Section: Impact On Belief Revisionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modeling culture in intelligent virtual agents

Mascarenhas

Degens

Paiva

et al. 2015

Auton Agent Multi-Agent Syst

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“…Another agent model where culture affects decision-making is the model proposed by Solomon et al [10], which concerns the definition of specific cultural norms. The model allows defining links between specific actions (e.g.…”

Section: Related Workmentioning

confidence: 99%

Creating a World for Socio-Cultural Agents

Degens

Hofstede

Breen

et al. 2014

Lecture Notes in Computer Science

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Abstract.Creating agents that are capable of emulating similar sociocultural dynamics to those found in human interaction remains as one of the hardest challenges of artificial intelligence. This problem becomes particularly important when considering embodied agents that are meant to interact with humans in a believable and empathic manner. In this article, we introduce a conceptual model for socio-cultural agents, and, based on this model, we present a set of requirements for these agents to be capable of showing appropriate socio-cultural behaviour. Our model differentiates between three levels of instantiation: the interaction level, consisting of elements that may change depending on the people involved, the group level, consisting of elements that may change depending on the group affiliation of the people involved, and the society level, consisting of elements that may change depending on the cultural background of those involved. As such, we are able to have culture alter agents' social relationships rather than directly determining actions, allowing for virtual agents to act more appropriately in any social or cultural context.

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“…However, the majority of these are culture-specific to a real culture. For example, the Culturally Affected Behaviour (CAB) model (Solomon et al 2008) allows the encoding of specific ethnographic data on cultural norms, biases and stereotypes, which are used to influence the behaviour of agents. CUBE-G (Rehm et al 2007) focuses on the modeling and generation of appropriate nonverbal communication aspects of different national cultures.…”

Section: Introductionmentioning

confidence: 99%

Learning to Overcome Cultural Conflict through Engaging with Intelligent Agents in Synthetic Cultures

Hall

Tazzyman

Hume

et al. 2014

Int J Artif Intell Educ

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Providing opportunities for children to engage with intercultural learning has frequently focused on exposure to the ritual, celebrations and festivals of cultures, with the view that such experiences will result in greater acceptance of cultural differences. Intercultural conflict is often avoided, bringing as it does particular pedagogical, ethical and political dilemmas of which cultures we place in conflict in the multicultural classroom. In this paper we discuss an alternative approach, providing children with an interactive learning experience with synthetic cultures and characters. The agent architecture developed to enable intelligent agents to exhibit culturally appropriate affect and behaviours is outlined. MIXER, an experiential learning application developed for 9-11 year old children on intercultural conflict is described, highlighting the Int J Artif Intell Educ (2015) 25:291-317 DOI 10.1007/s40593-014

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A Language for Modeling Cultural Norms, Biases and Stereotypes for Human Behavior Models

Cited by 16 publications

References 18 publications

Modeling culture in intelligent virtual agents

Modeling culture in intelligent virtual agents

Creating a World for Socio-Cultural Agents

Learning to Overcome Cultural Conflict through Engaging with Intelligent Agents in Synthetic Cultures

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