Quantum decision making by social agents

The influence of additional information on the decision making of agents, who are interacting members of a society, is analyzed within the mathematical framework based on the use of quantum probabilities. The introduction of social interactions, which influence the decisions of individual agents, leads to a generalization of the quantum decision theory developed earlier by the authors for separate individuals. The generalized approach is free of the standard paradoxes of classical decision theory. This approach also explains the error-attenuation effects observed for the paradoxes occurring when decision makers, who are members of a society, consult with each other, increasing in this way the available mutual information. A precise correspondence between quantum decision theory and classical utility theory is formulated via the introduction of an intermediate probabilistic version of utility theory of a novel form, which obeys the requirement that zero-utility prospects should have zero probability weights.Comment: This paper has been withdrawn by the authors because a much extended and improved version has been submitted as arXiv:1510.02686 under the new title "Role of information in decision making of social agents

Capturing Social Embeddedness: a constructivist approach

A constructivist approach is applied to characterising social embeddedness and to the design of a simulation of social agents which displays the social embedding of agents. Social embeddedness is defined as the extent to which modelling the behaviour of an agent requires the inclusion of the society of agents as a whole. Possible effects of social embedding and ways to check for it are discussed briefly. A model of co-developing agents is exhibited, which is an extension of Brian Arthur's `El Farol Bar' model, but extended to include learning based upon a GP algorithm and the introduction of communication. Some indicators of social embedding are analysed and some possible causes of social embedding are discussed

Expressing social attitudes in virtual agents for social training games

The use of virtual agents in social coaching has increased rapidly in the last decade. In order to train the user in different situations than can occur in real life, the virtual agent should be able to express different social attitudes. In this paper, we propose a model of social attitudes that enables a virtual agent to reason on the appropriate social attitude to express during the interaction with a user given the course of the interaction, but also the emotions, mood and personality of the agent. Moreover, the model enables the virtual agent to display its social attitude through its non-verbal behaviour. The proposed model has been developed in the context of job interview simulation. The methodology used to develop such a model combined a theoretical and an empirical approach. Indeed, the model is based both on the literature in Human and Social Sciences on social attitudes but also on the analysis of an audiovisual corpus of job interviews and on post-hoc interviews with the recruiters on their expressed attitudes during the job interview

Embedding Robotic Agents in the Social Environment

This paper discusses the interactive vision approach, which advocates using knowledge from the human sciences on the structure and dynamics of human-human interaction in the development of machine vision systems and interactive robots. While this approach is discussed generally, the particular case of the system being developed for the Aurora project (which aims to produce a robot to be used as a tool in the therapy of children with autism) is especially considered, with description of the design of the machine vision system being employed and discussion of ideas from the human sciences with particular reference to the Aurora system. An example architecture for a simple interactive agent, which will likely form the basis for the first implementation of this system, is briefly described and a description of hardware used for the Aurora system is given.Peer reviewe

Spatial Mobility in the Formation of Agent-Based Economic Networks

We extend the model of spatial social network formation of Johnson and Gilles (Review of Economic Design, 2000, 5, 273-299) by situating each economic agent within one of a set of discrete spatial locations and allowing agents to maximise the utility that they gain from their direct and indirect social contacts by relocating, in addition to forming or breaking social links. This enables the exploration of scenarios in which agents are able to alter the distance between themselves and other agents at some cost. Agents in this model might represent countries, firms or individuals, with the distance between a pair of agents representing geographical, social or individual differences. The network of social relationships characterises some form of self-organised persistent interaction such as trade agreements or friendship patterns. By varying the distance-dependent costs of relocation and maintaining social relationships we are able to identify conditions that promote the formation of spatial organisations and network configurations that are pairwise stable and efficient. We also examine the associated patterns in individual and aggregate agent behaviour. We find that both relative location and the order in which agents are allowed to act can drastically affect individual utility. These traits are found to be robust to random perturbations

Philosophers and Scientists Are Social Epistemic Agents

In this paper, I reply to Markus Arnold’s comment and Amanda Bryant’s comment on my work “Can Kuhn’s Taxonomic Incommensurability be an Image of Science?” in Moti Mizrahi’s edited collection, The Kuhnian Image of Science: Time for a Decisive Transformation?. Philosophers and scientists are social epistemic agents. As such, they ought to behave in accordance with epistemic norms governing the behavior of social epistemic agents