IJUP08 - Universidade do Porto

What can a simulation study tell us about the relevance of utility
and wealth indicators for decision making concerning production
and market behaviour
Frederico Teixeira 1 and Pavel B. Brazdil 1,2
1 Faculty of Economics, University of Porto, Portugal
2 LIAAD – INESC Porto L.A., University of Porto, Portugal
In this article we discuss the importance of utility as a crucial parameter for economic
decisions, in addiction to the more common parameter wealth. The work presented can be
seen as belonging to the area of Computational Economics [1] and has been inspired by the
work of Wellman [2].
Our study involves a simulated world with several agents which interact through a market.
The agents have different quantities of different types of products, and its behaviour is
driven by the goal to maximize the utility measure. This is calculated in an usual way [2]
and takes into account the basket of goods detained by each agent. Wealth is calculated by
simply multiplying basket quantities by current prices. An auctioneer determines the
appropriate current price using several iterations, until equilibrium is established. In order
to achieve their goal, agents exchange goods at the end of each period, and initiate a new
period of production and consumption. Each agent produces only one type of product, but
consumes certain quantities of all products. Production can increase/decrease by a fixed or
proportional amount, while consumption is fixed.
Our goal was to examine the trend of wealth and utility over time under different
conditions, including, for instance, under-production of all goods. We have focused our
attention on wealth, as normally this parameter is suggested for the control of production.
We have verified that when fewer products are produced, the agents’ wealth remains more
or less the same. The agents own less quantities, but those achieve higher prices. Surely,
this is not a satisfactory situation for any of the agents and so we conclude that the
parameter wealth by itself does not provide sufficient information to control production in
a satisfactory manner. Furthermore, we carried out some experiments in which production
was varied in a random manner, and observed that was possible to increase both wealth
and utility. So, utility could help solving the problem.
We conclude that utility and wealth can have different behaviours in identical situations,
but that it is possible to increase both at a time, meaning that it is necessary to analyze
them together and create rules that efficiently describes the agents’ global situation. Our
future aim is to try different strategies that an agent could adopt regards production, using
machine learning or other adaptive techniques to develop such rules. We intend to evaluate
whether the information concerning the agents’ utility (i.e. not only wealth) is useful when
controlling production, leading to better results overall.
References
[1] Tesfatsion, Leigh, K.Judd: Handbook of Computational Economics, Agent-based
Computational Economics, Volume 2, North Holland, 2006.
[2] Wellman, M., J.Hu: Conjectural Equilibrium in Multiagent Learning, Machine Learning, 33-
2/3, 1998.
5