Article Preview
TopOne important part of cognitive processes is decision making. As defined in (Wang, & Ruhe, 2007), “decision making is a process that chooses a preferred option or a course of actions from among a set of alternatives on the basis of given criteria or strategies”. Obviously, decision making is also a complex issue itself, requiring different types of techniques for the different aspects it requires. In this article we will concentrate on developing a formal framework to describe the exchange of goods (either material or intangibles) among entities, assuming that each entity can describe its own preferences.
In particular, our approach will be based on using an agent-based system. The reason is that these systems have already proved their usefulness to deal with cognitive environments (see e.g. (Yang, Lin, & Lin, 2006; Vinh, 2009; Uchiya, Maemura, Hara, Sugawara, & Kinoshita, 2009)).
In our work, the concept of utility function is very useful. A utility function returns a real number for each possible basket of goods: The bigger this number is, the happier the owner is with this basket. Intuitively, agents should act by considering the corresponding utility function (see e.g. (Rasmusson & Janson, 1999; Eymann, 2001; Dastani, Jacobs, Jonker, & Treur, 2001; Lang, Torre, & Weydert, 2002; McGeachie & Doyle, 2002; Keppens & Shen, 2002; López, Núñez, Rodríguez, & Rubio, 2002)). Besides, a formal definition of the preferences provides the entity with some negotiation capacity when interacting with other entities (Kraus, 1997; Sandholm, 1998; Lomuscio,
Wooldridge, & Jennings, 2001). Let us remark that, in most cases, utility functions take a very simple form. For instance, they may indicate that an entity E is willing to exchange the item a by the items b and c. Our framework consists of a set of agents performing exchanges of goods. Let us remark that it is not necessary to reduce all the transactions to money. In fact, most cognitive transactions are not based on money. Thus, an exchange is made if the involved parties are happy with their new goods, where the goods can be either tangibles or intangibles.
Note that, as transactions do not require money, the framework allows a richer structure of exchanges. First, money could be considered as another good, so we do not lose anything. Second, suppose a very simple circular situation where for each 1 ≤ i ≤ r, agent Ai owns the good ai and desires the good a(i mod r)+1 (see Figure 1). This multi-agent transaction can be easily performed within this framework. On the contrary, it would not be so easy to perform it if these items must be first converted into money. In fact, in case items are to be converted into money, the agent who desires the most expensive item would be unable to obtain it. So, the whole exchange will be deadlocked, even though all the agents would get happier performing it. Actually, it could be thought that agents would be able to exchange the items provided that the price of all the items is the same, but in that case we are not really using money: If all the items have the same price, any item can be used as currency unit, and what we obtain is a barter environment where money is not needed. Moreover, in case the goods to be interchanged were intangible, the reduction to money would be quite complex.
Figure 1. Exchange of items in the presence of circular dependencies