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.
The goal of this paper is to propose a method of modelling the evolution of social norms in different cultural settings. We analyse the role of culture in shaping agents' normative reasoning and hence their behaviour. The general notion of 'value' is discussed from the perspective of the BDI framework as a means to represent cultural regularities in social interactions. Culture is described as a system of shared values, which are linked to the Hofstede dimensions of culture. This system is represented by so-called metanorms that define appropriate, culturally-varying, behaviour in different relational contexts. In this way culture affects the possibility of normative changes, in particular the acceptance of policies designed to issue new norms in a society. Throughout the paper a scenario related to the enactment of smoking ban policies in Europe is presented to discuss the evaluation of normative change in specific cultural settings.
We simulate a closed rental housing market with search and matching frictions, in which both landlord and tenant agents are imperfectly informed of the characteristics of the market. Landlords, who observe a random sample of market offered rents, decide what rent to post based on the expected effect of the rent on the time-on-the-market (TOM) required to find a tenant. Tenants are heterogeneous in income. Each tenant observes their idiosyncratic preference for a random offer and decides whether to accept the offer or continue searching, based on their imperfect knowledge of the offered ret distribution.The steady state to which the simulation evolves shows price dispersion, nonzero search times and vacancies. We further assess the effects of increasing information on either side of the market. Tenants' information level has a positive effect on their welfare. Conversely, landlords are better off when they have less information. In that case they underestimate the TOM and so the steady-state of the market moves to higher rents. However, when landlords with different levels of information are present on the market, the better informed are consistently better off.The model allows the analysis of the dynamics. It is observed that dynamic shocks to the discount rate can provoke overshoots in rent adjustments due in part to landlords use of outdated information in their rent posting decision.
Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. We simulate a closed rental housing market with search and matching frictions, in which both landlord and tenant agents may be imperfectly informed of the characteristics of the market. The model hypotheses are set so as to match a rent posting search model in the spirit of search models of the labor market. In the simulations, landlords decide what rent to post based on the expected effect of the rent on the time-on-the-market (TOM) required to find a tenant. Each tenant observes their idiosyncratic preference for a random offer and decides whether to accept the offer or continue searching, based on their imperfect knowledge of the distribution of offered rents. The steady state to which the simulation evolves shows price dispersion, nonzero search times and vacancies. We further assess the effects of altering the level of information for landlords. Landlords are better off when they have less information. In that case they underestimate the TOM and so the steady-state of the market moves to higher rents. However, when landlords with different levels of information are present on the market, the better informed are consistently better off. The model setup also allows the analysis of market dynamics. It is observed that dynamic shocks to the discount rate can provoke overshoots in rent adjustments due in part to landlords use of outdated information in their rent posting decision. Terms of use: Documents in
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