In this paper, we consider the use of i* for modelling social networks in the context of mega-urbanization and water resources. In particular, we discuss, mostly by way of example, issues that are special to this domain such as the need to explicitly model nature or a new kind of agent evolution. Another important issue is the usability of i* by scientists from di erent disciplines to model mega-urban scenarios without any background in programming or mathematical models.
In the literature megacities are characterized as cities with at least ve to ten
million residents. Because of their size, megacities are confronted with severe
problems regarding water quality. Especially in cities situated in less developed
countries where the government tends to be ine cient in providing proper
infrastructures for the fast growing urbanization. Those cities have large areas
with informal settlements, for example slums, which are not properly connected
to a water grid and much less to sewerage resulting in bad conditions for waste
disposal and pollution of various qualities. Other sources of water pollution are
factories and even agriculture within the urbanized areas [
Because of the size and the fast growth of megacities, it is hard to survey the very complex processes which in uence the water quality in such big urbanized regions. To better understand such processes the SiKAMUS3 project was originated to simulate the behaviour of inhabitants of megacities. During such a simulation the residents are represented by agents who do their work in a megacity while consuming and polluting water.
The project is based on the multi-agent simulation framework SNet [
Since the domain experts in our project are hydrogeologists, who often have little background in formal methods (as understood in computer science), another objective is to provide a user-friendly interface to make it possible for those researchers to model and simulate di erent hydrological megacity scenarios without the need for aid from computer scientists or mathematicians.
In the next section we brie y outline, mainly by way of a small example, rst thoughts on how to use and extend SR diagrams to capture our application domain. We then highlight a number of other i*-related issues that are currently under investigation or still need to be addressed in the future. 2
In our application domain the main use of i* SR diagrams is to model the relationships between residents of a megacity and their in uence on water resources. In the future, this modelling should be done by geologists and urban planners to improve the water quality in megacities. We think that i* is a proper tool for these users because it avoids programming simulations.
The typical use of i* lies in the early phases of requirements engineering, where the actors can be both humans and technical artifacts such as software systems. In the context of megacities we are mainly dealing with human actors whose behaviour in uences the environment they inhabit. The relationships between humans can in principle be modelled by i*, but as we will see below there are novel features which may call for an extension of the formalism. Since the environment (nature) plays a central role in our domain, there is also the question how to model nature and its interaction with humans.
In order to use the SNet simulation framework for megacity scenarios we had to adapt the i* dialect used in SNet. In Figure 1 we see an i* diagram for a small fragment of our application scenario. It depicts the relationship between water users and local water suppliers in a megacity like Hyderabad: A water user tries to get water with a good quality from a reliable resource. She gets the water from a local water supplier who gets the water from a natural resource and maintains a water grid to distribute the water. If the water quality tends to be on a low level, a number of water users may join forces to exert pressure on the water supplier to raise the water quality.
In Figure 1 we used links between agents like in SNet. One of these links used by SNet is the softgoal contribution link. An example for that is the link from the task \improve infrastructure" to the softgoal \supply reliability", which means that an improvement of the infrastructure contributes to the reliability of the water supply. Another SNet link between agents is the decomposition link between the task \accept quality" and \supply water" which, in SNet, means delegating a task to another agent. However, in our domain of megacities such links are better understood as demands. For instance, if a water user accepts the quality of the water, she rather demands water from the local water supplier instead of delegating the task \supply water". Finally, we use SNet links to and from the triangle in the diagram in Figure 1 which is called precondition-e ect element in SNet. That is, if the task \complain about quality", the precondition, is ful lled, a value representing the discontent with the water supply is raised. If then a certain threshold for discontent is exceeded, the e ect is that the task \gather a ected people" can be performed.
This means that any water user who complains about the water quality raises the discontent which eventually leads to gathering a ected people. If we model it like that, the repeated complaining of one water user is enough to gather a ected people. But if we want that gathering people needs more than one water user, there is no obvious way to model this. For that reason we decided to enhance i* to be able to express that we need more than one agent for issues like raising discontent. In particular, we propose something similar to cardinalities in entityrelationship diagrams. The \50..N" next to the arrow towards the preconditione ect element indicates that more than fty di erent agents must be discontented until the e ect can occur. Note that this is another kind of threshold than in the precondition-e ect elements themselves. There the threshold concerns the quantity of the subject of the element; here discontent. The cardinalities indicate that the e ect occurs only if this threshold is exceeded by raising the discontent by, in this case, at least 50 di erent agents.
Furthermore, to model hydrological scenarios in a megacity we need something to represent nature. That is necessary because we have natural resources like groundwater and natural phenomenons like rain and oods which in uence the water level and quality.
In the middle of the diagram in Figure 1 we see a green octagon which is a proposal for a new element. An interesting question is: what kind of resource is the water resource? The problem here is that water is not provided by an agent; it is a natural resource. Furthermore, it is in uenced by natural forces like rain. On the other hand, it is in uenced by the behaviour of the citizens of a megacity. For instance, the water can be contaminated by waste from informal households and production processes. On the other side, the government can manage to build a water grid and sewerage to raise the quality of the water resources. Because the resource is not provided by some agent and is in uenced by many others, we think that we cannot use the original i* resource element for natural resources. Therefore, we propose a new element whose rst version is the green octagon in Figure 1. The link from this element to the task \supply water" means that this task is only possible to perform if the water resource provides water.
In addition, in Figure 1 we also use resources which are provided from agents rather than from nature. For instance, the link to the resource element \funds" in the diagram means that the water users raise the funds by paying their water bills. Furthermore, the links from \funds" to the tasks \maintain water grid" and \supply water" mean that these tasks can only be performed if the funds are su cient. The nature resources as well as these resources are not used in SNet.
Finally, a problem occurring in modelling megacities is that diagrams soon become very large, often with many links between elements, which users nd confusing. For that reason we need a proper approach to make such big diagrams manageable. A rst attempt to overcome this problem can be seen in the income resource in Figure 1. We propose to modularize the diagram by connecting separate diagrams with linking elements in the diagram linking to other diagrams. The small arrow at the right upper corner at the resource element indicates a link to the diagram with the provider of this resource.
In conclusion, i* appears to be a promising tool for modelling actors and their interdependencies in megacities, but some additional features may be needed for this purpose.
As in SNet the i* diagrams serve as input for a translation into ConGolog
programs, whose execution generate simulations for particular instantiations of the
given network. In our case additional information is provided by geodata which
describes the surroundings of agents in a megacity. In particular, we make use of
existing data about groundwater quality, water management and urban growth
in megacities like Hyderabad (India), Guangzhou (China) and Yogyakarta4
(Indonesia) [
While the information contained in the OWL database is crucial to obtain faithful simulations, it is unclear at this point how much of the OWL ontology needs to be re ected in the i* model. 3
We are in the middle of investigating how we can model megacities. Therefore, the proposed adaptations of i* are likely not the nal versions. To complete our work we still have to consider the following.
For instance, if we think about natural phenomenons, we can also think about representing nature as an actor. But in contrast to the predominant view in i*, this actor acts according to natural laws and without intentions.
This notion of nature then can provide natural resources. The work is still in progress, so we have no complete concept for this ready. Furthermore, we still need a semantics for natural elements. Since, as mentioned above, the ontology stored in an OWL database determines the surrounding of an agent, we think the semantics of natural elements has to follow the structure in the OWL ontology. For example, if we instantiate the water resource element in Figure 1, we dispose where an agent is situated in the megacity and depending on this we set the availability of this resource.
Furthermore, the third role in the diagram in Figure 1 besides \local water
supplier" and \water user" is \water quality activism." This should be played
by some agent who exerts in uence on the water supplier and gathers people
to raise the pressure. But if we think about people who complain about the
government, it must be more than one agent which plays this role. In addition,
these have to be the same agents which play the role \water user." For this,
agents have to change their roles; it should be possible that a water user becomes
an activist. Roesli et al. [
To modularize huge diagrams we proposed linking elements which connect
separated diagrams. Alencar et al. [
In this paper we highlighted a number of issues that arise from using i* to model actors in mega-urban cities with a focus on water resources. In many ways we have only scratched the surface of the problems in this interesting domain. In the future we hope to report on new ndings, also regarding our long-term goal of simulating agents in mega-urban scenarios.