a cultural decision making model for virtual agents

Application to the Ultimatum Game

Two turn game: Two players can split a certain amount of money. Proposer: make an o�er (here from 0 to 100)Responder: accept or reject the o�er

Possible Outcomes:If accepted – money is split according to dealIf rejected both get nothing

A Cultural Decision Making Model for Virtual AgentsComputer Science Department, USC

Model’s Cultural Working Paradigm

Modeling Culture

Hofstede's proposed a dimensional model for culture based on the following dimensions: Masculinity (MAS), Individuality (IDV), Power Distance (PDI), Uncertainty Avoidance (UAI), Long Term Orientation (LTO) (Hofstede, 2001).

We use cultural dimensional scores to contribute to the weight of each valuation . The weight of each valuation function is the product of the contirbution of each individual cultural dimen-sion.

Our Model

Our model has a multi attribute paradigm: and takes into account several metrics other than self interest:

1. Self Interest (the agent's own utility)2. Other Interest (the utility of other parties involved)3. Total Utility (sum of individual utilities of all parties)4. Average Utility 5. Relative Utilities (viewed in several ways, such as self/total, self-other, self/other, self/average)6. Minimum Utility (lower bound for any participant - Rawls' theory of justice)

Motivation

Most classical economic game-theory accounts of decision-making look at a monolithic notion of utility and maximizing expected utility as the key to rationality. However, it has been shown by social scientists that in practice game-theory models cannot predict how people make deci-sions and that people from di�erent cultures behave di�erently in interactive situations (Camerer, 2003).

Our Goals

In order to build agents that can interact with humans we need to have a model that is good at replicating human behvaior. We want to build a decision-making model that can:

a) replicate human behavior taking into account more than just Self-Utilityb) capture cultural di�erences in the behavior of people from di�erent backgroundsc) be incorporated into virtual agents

Elnaz Nouri, David Traum

Human playing ultimatum game with virtual agentVirtual agents playing ultimatum game

Comparison of the model results with humans playing ultimatum game

Results

Summary

We build a novel decision-making model thata) takes into account multiple valuations of a decisionb) captures di�erent ways of evaluating the same choice set across di�erent circumstancesc) takes into account individual and group di�erences in culturesd) is useful for modeling decision making in virtual humans interacting with each other and with real humanse) is explicit enough to implement and cover common situations

Future Work

a) Learn the weights using machine learning techniques, e.g. inverse reinforcement learning.b) Verify the hand-crafted rules.c) Incorporate into our model information about emotions, personality, and dialogue context. d) Focus on cultural di�erences with respect to persuasion.

References

Nouri, E., & Traum, D. (2011). A cultural decision-making model for virtual agents playing negotiation games. In Proceedings of the International Workshop on Culturally Motivated Virtual Characters. Reykjavik, IcelandCamerer, C. F. (2003). Behavioral game theory - Experiments in strategic interaction. Princeton University Press.Hofstede, G. H. (2001). Culture’s consequences: Comparing values, behaviors, institutions, and organizations across nations. Thousand Oaks, CA: SAGE.

Acceptance RatioO�er distribution

Four Di�erent Cultures

Human - US Culture

Cultural Background A�ects Decision Making

Rational Self Interested Agent

Observed Behavior in Game

Incorporating our Model into Virtual Agents

General Table of Weights Example: Hand crafted MAS weights

Setting the Model Weights

Culture PDI IDV MAS UAIVirtual Human Mean Offer

Human Mean Offer

Virtual Human Rejection Rate

Human Rejection Rate

Hofstede's Dimensional Values Israel 13 54 47 81 $21.66 $41.71 25% 17.70%Japan 54 46 95 92 $32.50 $44.73 1% 19.30%Chile 63 23 28 86 $33.13 $34.00 1% 6.70%Austria 11 55 79 70 $33.13 $39.21 9.10% 16.10%Ecuador 78 8 63 67 $33.13 $34.50 1% 7.50%Germany 31 64 61 60 $36.88 $36.70 9.10% 9.50%US 40 91 62 46 $41.88 $42.25 12.00% 17.20%Spain 57 51 42 86 $28.75 $26.66 25.00% 29.20%Sweden 34 70 4 26 $33.13 $35.33 10.20% 18.20%