DISEÑO DE LA PLACA EXPULSORA

Up to this point, we have presented strategies that use service evaluation, dependence, or exchange values individually to select providers. However, these criteria are comple- mentary, and thus can be combined in a mixed strategy. By complementary we mean that, to find candidate providers more likely to accept requests, information about the requester’s credit value and dependence in relation to each provider can be combined, so that when the requester does not have any credit with the candidate providers it can use information about dependence. Similarly, to find interactions with a potentially better outcome in terms of the quality of the received service and balance of gains and losses, information about service evaluation and balance of exchange values can be combined. This information is complementary, since service evaluation is an objective measure for service quality, and the balance of exchange values is relative to both objective and subjective values.

To combine these different criteria in order to determine which providers are at the same time more likely to cooperate and more likely to yield a successful interaction, the combined strategy is defined such that providers are ranked according to each separately,

and then both results are aggregated in a single ranking of preferred providers4. This

process is detailed in Algorithm 14, in which providers more likely to cooperate are

ordered in sequence Pcop, providers more likely to yield a successful interaction are

ordered in sequencePsuc, and the final preferred providers are ordered in sequence Po.

The sequence Psuc is ordered with providers with higher service evaluations first (that

is, P eval(αi) > P eval(αi+1)). If evaluations from two consecutive candidate providers

4

This technique is similar to the Borda count voting protocol, which is used to choose an agent from a group of candidates for performing some task, based on the preferences of a distinct group of agents (the voters). To determine the winner candidate based on the majority of votes, the protocol consists of assigning points to candidates in each voter’s preference list according to their position in the list, and summing these points across voters to find the candidate with the highest points total (Sandholm, 1999).

Table 7.2: Scoring Candidate Providers According to Ordering Criteria for Psuc.

αi P eval(αi) oabnαi Score

α1 0.8 4

α2 0.6 3

α3 0 0 2

α4 0 50 1

Table 7.3: Scoring Candidate Providers According to Ordering Criteria forPcop.

αi totalv_βαi>0 αi ∈Dbd Score

α1 true true 4

α2 true f alse 3

α4 f alse true 2

α3 f alse f alse 1

inPsuc are the same, preference is given to the one with fewer negative overall balances

of exchange values in previous interactions (oabn_αi < oabn_αi+1). Service evaluation and

the proportion of negative overall balances are considered here as quantitative criteria,

and a service evaluation P eval(αi) for each candidate provider αi is calculated as in

Section 7.4.1. The sequence Pcop is ordered with providers with which the requester

has credit first (with totalvβαi > 0). If the credits from two consecutive candidate

providers in Pcop are zero, preference is given to the one with which the requester has

a mutual dependence (that is, αi ∈Dbd). Credits and dependence are considered here

asqualitative criteria, in the sense that quantities are not taken into account, but only whether a credit is greater than or equal to zero, and a dependence is true or false. This improves the combination of the two sequences, since we assume that having a credit with a provider (regardless of the quantity) is already an indication that this provider

is more likely to reciprocate, so when the two rankings (Psuc and Pcop) are combined

and the requester has credit with two different providers, the one which is earlier inPsuc

(and thus more likely to provide a good service) is preferred.

After sequencesPcopandPsucare ordered, a score is assigned to each candidate provider

according to each set’s ordering criteria. The highest score is the number of candidate

providers in P (|P|). Candidate providers in Psuc receive scores according to their

position in the sequence (since the ordering criteria for this set are quantitative), with scores decrease by 1 as agents get further from the first position in the ordered sequence,

as shown in Table 7.2. Candidate providers inPcop receive scores depending on whether

they satisfy each ordering criteria, such that the highest score |P| is assigned to all

agents that satisfy both totalv_βαi >0 and αi ∈Dbd, the score |P| −1 is assigned to all

agents that satisfy only totalv_βαi > 0, the score |P| −2 is assigned to all agents that

satisfy onlyαi∈Dbd, and the score|P| −3 is assigned to all agents that do not satisfy

both criteria. Note that the score for agents that satisfy only totalv_βαi > 0 is higher

than the score for agents that satisfy onlyαi ∈Dbd, since the former criterion is applied

of scores for the elements of Pcop when|P|= 4 is shown in Table 7.3.

The final sequence Po of preferred providers is ordered according to the total score of

each candidate providerαiin bothPcopandPsuc(represented in Algorithm 14 asS[αi]).

For example, consider four providersP ={α1, .., α4} that are ordered in Pcop and Psuc

as in Tables 7.3 and 7.2. The score for α1 is 8 (4 + 4), for α2 is 6 (3 + 3), for α3 is

3 (2 + 1), and for α4 is 3 (1 + 2), which results in the sequence of preferred providers

Po = hα1, α2,{α3, α4}i. If two providers receive the same score, the requester may

choose the one that has higher score either on sequence Pcop, if the requester is more

concerned with the time taken to find an available provider, or on sequence Psuc, if it

is more concerned with the success of the interaction. In the end, the ordered sequence

Po represents providers that are, at the same time, more likely to provide good services

and to accept requests.

7.5

Conclusion

In this chapter, we have presented a provider selection mechanism for service requesters operating in dynamic cooperative applications. The mechanism addresses two problems: first of selecting a service provider that performs a good quality service from among alter- natives providing similar services; and second of finding providers more likely to accept requests so that requests do not take a long time to be accepted. This is achieved by considering, as selection criteria, information on both previous evaluations of services and reciprocal relationships with other agents, through service dependence, service eval- uation, and exchange values.

From these selection criteria, exchange values provide the only criterion that allows the analysis of both service quality (through the satisfaction value and the balances of exchange values) and reciprocal relationships (through the credit value).

Five provider selection strategies that combine different criteria have been proposed. Some focus on one aspect of the providers, while others try to balance selection accord- ing to both aspects: service quality and reciprocal relationships. Based on the strategies’ design properties, we expect that the latter strategies, represented here by the exchange

values-based analysing cooperative situations and combined strategies, can improve the

performance of agents in the task of finding providers for the services that they need, when they operate in open cooperative systems in which providers are resource con- strained, and services are free and have different levels of quality.

Requester Selection Mechanism