IDK and ICARO: developing Multi-agent Systems in support of Ambient Intelligence
José M. Gascueña a, Elena Navarro a,b, Antonio Fernández-Caballero a,b, Patricia Fernández-Sotos c and Juan Pavón d a Instituto de Investigación en Informática de Albacete (I3A), 02071-Albacete, Spain b Universidad de Castilla-La Mancha, Departamento de Sistemas Informáticos, 02071-Albacete, Spain E-mail: {Elena.Navarro, Antonio.Fdez}@uclm.es c Universidad de Castilla-La Mancha, Facultad de Medicina, 02071-Albacete, Spain d Universidad Complutense de Madrid, Facultad de Informática, Departamento de Ingeniería del Software e Inteligencia Artificial, c/ Profesor José García Santesmases, s/n, 28040-Madrid, Spain
AbstractAn important component of Ambient Intelligence (AmI) is the massive deployment of a new generation of intelligent agents, embedded in the environment and adaptive to the users’ profiles, preferences and needs. That is why, the use of agent- oriented methodologies and frameworks is almost mandatory to easily develop software for AmI scenarios. ICARO is a software framework that promotes the use of different organizational and behavioral patterns to implement multi-agent systems (MAS). Its extensive use in several projects demonstrates a substantial increase in software productivity. Also, in order to reduce the coding effort it is usual to design MAS at a higher level. In this sense, code generation from MAS specifications into ICARO framework has been performed. INGENIAS Development Kit (IDK) supports both the specification of MAS models, including any feature required to implement MAS with ICARO, and a set of facilities for code generation. This paper describes the development of AmI applications thanks to the integration of ICARO and IDK. Two IDK modules have been developed, namely a “code generator” and “code update” module.
Keywords: Multi-agent systems, Agent-oriented software engineering, Code generation, Ambient Intelligence, Assisted living systems, Ambient assisted systems, Smart homes.
1. Introduction has opened the door to its exploitation in a wide variety of previously unforeseen systems. For instance, it is Ambient Intelligence (AmI) is being a very active being widely exploited in the context of smart homes, topic of research in the last decade. Ducatel et al. [14] also called ambient assisted systems and assisted living envisioned some of the ideal scenarios that AmI should systems. They are home-like environments that exploit be able to offer to the society, community as well as AmI to respond to the behavior of their residents and individuals. As stated by the authors, AmI promotes to provide them with novel services and facilities [13]. the development of innovative and intelligent user in- Home care is one major category of smart home ap- terfaces “embedded in an environment that is capable plication. Some systems have been developed for de- of recognizing and responding to the presence of dif- ferent individuals in a seamless, unobtrusive and often tecting falls of elders by processing the information of invisible way”. AmI user interfaces become transpar- sensor infrastructures [37]. Other interesting systems ent (people do not perceive complexity neither pres- are being applied in the context of health-care to de- ence) and they are “intelligent” to react in a proac- tect problems such as heart breaks by processing con- tive and sensitive way [1] at the same time. The idea text information [11]. These systems target at elders to of making technology transparent but usable to people provide them with independence and quality of life. 2 J.M. Gascueña et al. / ICARO in support of AmI
sign phases. With this aim in mind, ICARO provides engineers with concepts and models, together with a customizable MAS design, Java code fully compati- ble with software engineering standardsas Also, it can be integrated into the most popular integrated devel- opment environments (IDE). Moreover, it is indepen- dent of the agent architecture, this way enabling de- velopers to create new architectures and integrate them into the framework. This is a clear difference with re- gard to other agent frameworks, such as JACK [40] Figure 1. AmI system interacting with its environment. or JADE [4], as they provide a middleware instead of an extensible architecture to establish the communica- AmI systems take advantage of Artificial Intelli- tions among agents. This advantage provides develop- gence (AI) techniques as the means to resemble hu- ers with the necessary flexibility to deal with the di- mans when interacting with their environment. For this versity of AmI devices and communication technolo- reason, an AmI system perceives the state of the users gies. An additional advantage is that the framework al- and/or the environment, reasons about the collected ready implements functionality for automatic compo- data by using AI techniques such as intelligent agents, nent management, application initialization and shut- and acts accordingly to achieve the expected goals down. This reduces the developers’ workload and en- (see Fig. 1). Moreover, agents are a good in model- sures that all components are under control. This last ing, simulating, and representing meaningful entities functionality is not usually provided by other frame- such as rooms and persons in AmI systems [34]. The works. AmI systems properties turn their development into a The rest of the article is organized as follows. Sec- challenging work demanding adequate tools that assist tion 2 describes the related work. Then, section 3 intro- throughout a well established software development duces IDK modules developed for ICARO. After that, process. Both tools and process should be able to adapt a case study illustrates our approach in section 4. Fi- to the diversity of AmI devices and communication nally, some conclusions are provided in section 5. technologies from an implementation point of view. The major contribution of this paper is to introduce our experience after developing couple of software mod- 2. Related work ules facing the mentioned issues. The software con- sists in a code generator module and module to support As stated by Cook et al. [10] AmI technologies are code update. The modules have not been developed expected to be sensitive, responsive, adaptive, trans- from scratch but INGENIAS Development Kit (IDK) parent, ubiquitous, and intelligent. The three first fea- [20], the tool supporting the agent-oriented software tures greatly rely on the context-aware computing engineering methodology named INGENIAS [31], has field, but transparency and ubiquity depend on the area been used. IDK provides a template-based proprietary of ubiquitous computing, also called pervasive com- mechanism for developing new modules which auto- puting. But it is intelligence which becomes a criti- matically generate code for any target language. As far cal feature as it makes AmI systems more sensitive, as we know this functionality is not provided by any responsive, adaptive, transparent and ubiquitous. The other tool dedicated to designing multi-agent systems main reason is that the intelligence feature helps in un- (MAS) (e.g. Prometheus Design Tool (PDT) [30], Tool derstanding user environments and, consequently, in for Agent Oriented visual Modeling for the Eclipse providing them adaptive assistance [9]. This explains platform (Taom4E) [26] or DSML4MAS development why AmI entails contributions from different AI areas, environment (DDE) [38]). such as machine learning [3], ontologies [24], neu- The two aforementioned modules generate code for ral networks [9] and, specially, multi-agents systems ICARO framework that provides high-level software (MAS). components to facilitate the development agent-based Indeed, MAS are especially good at modeling real- applications. Moreover, it promotes the use of differ- world and social systems, where problems are solved ent organizational and behavioral patterns that enable in a concurrent and cooperative way without the the specification of MAS at a higher level during de- need of reaching optimal solutions [34]. Indeed, AmI J.M. Gascueña et al. / ICARO in support of AmI 3 proposes the development of context aware systems A clear alternative is ICARO which provides pat- equipped with devices that recognize context and act terns to build reactive [18] and cognitive [22] agents. accordingly. Agents provide an effective way to de- The use of component patterns for modeling MAS velop such systems since agents are reactive, proac- is a differentiating factor from other agent-oriented tive and exhibit an intelligent and autonomous behav- programming frameworks and languages [5]. More- ior [2]. Agents react to humans based on information over, while other agent-based platforms that are FIPA- obtained by sensors and their knowledge about human compliant (e.g. JADE) focus mainly on communica- behaviors within AmI applications [6]. tion standards, ICARO targets on providing high-level As aforementioned, the development of AmI sys- software components for easy development of com- tems is not a trivial issue, being necessary the use of plex agent behavior, agent coordination, and MAS or- tools and well-defined processes that guide the stake- ganization. Regrettably, to date there are no tools for holders. Taken into account the relevance that MAS modeling MAS applications and generating code for has to AmI, several alternatives providing the neces- this framework. So, there is a need for code generation sary support have recently been developed. One of from design specifications to ICARO framework. them is the methodology defined by Serrano et al. [36], Code generators are useful tools for software de- based on the use of MAS-oriented simulations for the velopment due to the evident benefits provided by validation of AmI-based ubiquitous computing sys- their exploitation [29], [15]. One of these benefits is tems. This proposal is very interesting as it helps to an improved productivity since the time necessary validate AmI applications whose real tests would be to perform coding tasks is reduced. Another impor- impractical because of the unavailability of resources, tant benefit is that the quality of the developed sys- high cost, and so on. Unfortunately, the methodology tems is also improved, as the generated code (usu- ally) does not have bugs. MAS are not an exception only provides guidelines for validation purposes and to this rule. Several tools for developing MAS appli- not for the whole development of AmI systems; so it cations [33] already provide functionality to gener- has to be used jointly with other proposals. Muñoz et ate code for a given agent programming language or al. [28] present an argumentative multi-agent architec- framework. For example, the supporting tool of the ture that exploits semantic web ontologies to discover Prometheus methodology offers a code generation fa- inconsistent contexts, but the approach does not offer cility to automatically produce JACK agent language a complete support for the development of AmI sys- code [40]. Taom4E [27], a tool for the development tems from an implementation point of view. Yi-bin et of software following the TROPOS methodology [26], al. [41] have also defined a set of models applicable includes functionality to generate code for Jadex lan- for design and development that unfortunately cannot guage [8]. DDE [38] is an environment for the devel- be extended to provide the necessary flexibility. Ayala opment of MAS that is based on a Domain Specific et al. [2] have recently developed a platform-neutral Modeling Language for MAS and supports code gen- framework called MalacaTiny. It is a quite power- eration for JACK and JADE languages [4]. Another ful framework which manages the diversity of com- proposal develops a code generator with MOFScript munication technologies by using aspect-oriented pro- (see http://marketplace.eclipse.org/content/mofscript- gramming. However, it has been specifically designed model-transformation-tool)that transforms agent mod- for mobile applications so that its capabilities to de- els, compliant to its meta-model PIM4Agents, to code velop general AmI systems remain unexplored. Other for the MalacaTiny platform-neutral framework [2]. framework is JaCaMo [7], which encompasses a multi- Finally, our code generator was developed with IDK dimensional concept (organization, agent and environ- [20]. Several reasons led us to this decision. First, it ment) to develop MAS. Unfortunately, the JaCaMo re- offers a graphical editor for modeling MAS applica- lated agent programming language uses BDI [35] con- tions and functionality for developing new modules cepts, reducing its reusability in different applications. able to automatically generate code for any target lan- Although these proposals are relevant to the develop- guage. This graphical editor, generated from the IN- ment of AmI systems and provide great advantages, all GENIAS meta-model [31], can be extended introduc- of them experience some serious problems when they ing new concepts and relations needed to build new have to deal with two challenging issues at the imple- MAS applications. Afterwards, the IDK is regenerated mentation level, namely the diversity of AmI devices again from the new meta-model specification. An ad- and the variety of communication technologies. vantage of this approach is that changes in the defini- 4 J.M. Gascueña et al. / ICARO in support of AmI tion of the meta-model are easily applied to generate producer of the event and potential receivers. An event personalized editors, facilitating the needed flexibility is used for communication and information delivery for handling the inherent diversity of AmI systems. from a resource to its agent or among agents. Thus, Second, regarding the modules, they are developed fol- agents send events through their use interfaces and, in lowing a general process based on both the definition the same way, a resource also uses the use interface of of specific templates for each target platform and pro- an agent to send it an event. Second, an agent uses the cedures to retrieve information from INGENIAS mod- resource use interface to request the services (meth- els [19]. Currently, IDK incorporates modules to gen- ods) it offers. From our point of view, the concepts erate code for JADE language from design artifacts as of reactive application agent and application resource well as documentation in HTML format for these arti- used in ICARO can be modeled in INGENIAS by us- code uploader facts. Finally, a module named , which ing the concepts of agent and application, respectively. is used to keep the code components design artifacts For example, when establishing a relationship Appli- updated with changes made in the implementation, is cationBelongsTo between an agent and an application, also available. it is understood that the agent uses the services offered by the resource (see Fig. 2). In particular, the actions 3. IDK Modules for ICARO that agents execute on the environment are represented by this structure. Services are modeled as application The development of IDK modules has followed a methods. “bottom-up” approach to support ICARO as the tar- Sending information from a resource to an agent get platform chosen for the final implementation of a is modeled in INGENIAS by establishing a relation- MAS application. In first place, the INGENIAS struc- ship EPerceives between the agent and the applica- tures for specifying all concepts and their relations tion which represents the resource (see Fig. 3). In IN- which are necessary to implement an application in GENIAS, this information falls within the relationship ICARO are identified. Then, a module which auto- EPerceives that is modeled with an event of type Ap- mates the task of ICARO code generation from INGE- plicationEvent when a resource simply sends a signal NIAS specifications, in line with the identified concep- to the agent. But, it is modeled with an event of type tual relations, is gradually developed. Finally, a new ApplicationEventSlots when more information has to module upgrades the specification of a model when be sent. In the latter case, the information and its type there are changes in the implementation. A detailed is modeled with slots entities. description of the general process for developing IDK Now, sending information among reactive agents is modules can be found in [31]. The next subsections modeled in INGENIAS by specifying an entity of type provide a description about the relations between IN- InteractionUnit and relating it to the producer and con- GENIAS and ICARO concepts, as well as the develop- sumer agents by means of the UInitiates and UICol- ment of the modules to generate code for ICARO and laborates relationships, respectively (see Fig. 4). If to support the update of code, respectively. the producer sends information, then it is included in the interaction unit through an entity of type Frame- 3.1. Conceptual Relation between INGENIAS and Fact containing the necessary slots to transport it. Con- ICARO versely, if it only needs to send a signal, then the FrameFact First, it is worth explaining some details of the fig- is not included in the interaction unit.Vi- ures that describe the relationship between INGENIAS sually, it is possible to know that an interaction unit and ICARO. The right side of the figures correspond to includes a FrameFact because it shows the “Info” at- the notation chosen to express a fragment of a model tribute (the value shown is the identifier of the Frame- using ICARO concepts and the left side is the notation Fact). used to express the same fragment but in terms of the Whenever an ICARO user wants to implement the INGENIAS language. behavior of a reactive agent, he/she has to create an au- Any communication between the components im- tomaton which is modeled with a state diagram. In par- plemented to develop a new executable ICARO appli- ticular, five structures available in INGENIAS “state cation can be summarized as follows. First, an event diagram” and a criterion to name agents are needed to is an entity for exchanging information between the specify any automaton (see Fig. 5): J.M. Gascueña et al. / ICARO in support of AmI 5
Figure 2. Modeling an agent using resource’s services.
Figure 3. Modeling an agent’s perception.
Figure 4. Modeling a communication among agents.
– A relationship is established between an “Ini- Fig. 4). The semantic action takes the same name tialNode” entity and the state to represent the ini- as the task created in the components diagram. tial state. – The IDK tool does not enable to explicitly repre- – A relationship is established between an “EndNode” sent relationships that cycle over the same entity, entity and the state to represent a final state. so that a fourth structure has been considered.In – A “WFollowGuarded” relationship is established order to represent a transition that comes back to between two different states to represent a tran- the same state, first a copy of the state is made, af- sition; and a transition is specified using the syn- terwards a “WFollowGuarded” relation is estab- tax event / semantic action in its “Condition” at- lished from the copied state to the original state, tribute. The event represented in the state diagram and finally the transition is specified following the is related to an ApplicationEvent or an Applica- syntax described in the previous third structure. tionEventSlots entity when the event is sent by a – Universal transitions of an automaton of an ICARO resource (see Fig. 3). It is related to an Interactio- reactive agent are valid for any state of an automa- nUnit entity if the event is sent by an agent (see ton. That is to say, when the event arrives, actions 6 J.M. Gascueña et al. / ICARO in support of AmI
Figure 5. Modeling an agent’s automaton.
are executed and the next state is reached, regard- code for the ICARO framework. For this aim, the IIF- less of the automaton current state. The solution Generator class is extended so that its constructors for graphically representing them in INGENIAS possesses the templates that the IIF module uses in a is to have a “UniversalState” that represent any similar way to any other IDK code generator. More- state and takes the role of the “source” state of the over, the extended IIFGenerator class also implements universal transition. Obviously, “UniversalState” the abstract methods defined in BasicCodeGenera- has not to be used with a different meaning. torImp. It is worth noting that the development of the – Finally, notice that the agent’s name is assigned IIF module has been simplified by defining a template to the state diagram as a criterion to identify the for each artifact that an ICARO user has to implement agent’s behavior. (see Table 1). The XML file that describes the organization of The IDK templates for code generation contain an ICARO application represents its deployment. The source code written in the programming language of IDK tool offers the possibility of creating deployment the target platform and tags to establish where the diagrams. The number of instances of each type of model information is used during the generation of agent is specified using entities such as Deployment- code. The kinds of tags to be used in an IDK template Package and/or DeploymentUnitByType. However, the is very limited [19]: program is the main tag of the existence of an application instance is conditioned by document, repeat means that the text enclosed by this the existence of the instance of an agent. For this rea- tag has to be copied and pasted to have a duplicate, son, it is necessary to find an alternative way of inde- v represents a variable, and saveto is used to save the pendently expressing the number of instances of agents enclosed text into a file. Therefore, it can be stated that and applications, such as in ICARO. The solution is to the IDK code generation technology is more straight- create an environment model and to follow the follow- forward and easy to learn than other technologies for ing steps: (1) to copy all the agents and applications, code generation, such as XSLT [39] or XPAND [21]. (2) to relate them with entities of type UMLComment, However, IDK exhibits a disadvantage as it does not and (3) to set the number of instances to be deployed enable developers to reuse templates. They have to in the attribute Text of UMLComment. Obviously, this copy and paste the fragments to be reused, this way process can be repeated over and over to create differ- hindering the code generator maintainability. ent deployment configurations. Next, the elements used by the IIF module to gen- erate code for the intermediate states of an ICARO re- 3.2. Code Generation Module active agent automaton are shown. With this aim, the automaton template specifies the following pattern: for The IDK module named (INGENIAS ICARO Frame- each (first repeat) intermediate state defined by the in- work generator) IIF has been developed to generate termediateState variable, generate code for each (sec- J.M. Gascueña et al. / ICARO in support of AmI 7
Table 1 Description of the templates Template Description Automaton It is used to generate an xml file with the automata agents code. SemanticAction It is employed to generate code for the classes that implement the agents’ semantic action. ResourceGeneratorClass It is used to generate code for the classes that implement the resource use interfaces. The code of both methods and parameters of these classes is automatically generated as well. ResourceUseItf It is used to generate code for the resource use interfaces. Deployment It is employed to generate an xml file with the organization of the ICARO application under development. ond repeat) transition that starts with such intermediate facilities that prevent manually written code from be- state. ing overridden by subsequent generator runs. The so- @@@repeat id="intermediateStates"@@@ lution in IIF has been to integrate a facility for mark-
Figure 7. Environment model.
Figure 11. Deployment model.
Figure 8. Partial view of the Interaction model.
The personal health agent behavior concludes that an AMI might be happening and communicates this fact to a medical resource manager agent. The last agent selects the best MICU according to the geographical location of the human. Figure 12. Development of ICARO applications using IDK. As aforementioned, AmI systems have to monitor, reason and react. Monitoring of the health system as If heart rate > 100 Then Tachycardia; If heart rate < 60 Then Bradycardia; well its reaction can be specified through INGENIAS. If breaths per minute > 20 Then Tachypnea; If breaths per minute < 12 Then Bradypnea; Moreover, INGENIAS can be also used to model the ... behavior of the reactive agents through automata (state diagram). For example, the personal health agent re- So, a particular health problem is detected when an acts to the information related to the devices as sent by individual rule is satisfied. However, the interest of its other agents. Moreover, it is responsible for reasoning function increases when several conditions are simul- if any health problem is happening through the human taneously satisfied, because the integration of different health state by using different rules, such as: information sources allow to diagnose more complex 10 J.M. Gascueña et al. / ICARO in support of AmI
Figure 9. Interaction protocol.
Figure 10. Automaton of personal health agent. problems (as an AMI in the described scenario). The It is also necessary to specify another model for the personal health agent holds an initial state, a final state deployment of the application (see Fig. 11). For in- stance, this model would specify there is one instance and remains in an intermediate state to receive infor- for each type of agent related to a device, one instance mation sent by the agents related to the devices (see of personal health agent, one instance of medical re- Fig. 10). Each certain time a diagnosis is issued by the source manager agent, ten instances of MICU agents agent. and MicuGUI applications, and one instance for appli- J.M. Gascueña et al. / ICARO in support of AmI 11 cations of type UserDB and UserGUI for the described date) that provide support for the implementation of scenario. It is worth noting that the above described ICARO reactive agent applications has been described. models are just a partial view of the system, as they These modules are integrated in the IDK tool. It is would have to be extended to consider all its require- worth pointing out that the time spent learning how ments. For instance, this is the case in order to create to develop and implement the IIF and the ICAROT- new patients or to define additional reasoning. CodeUploader modules described in section 3 was two Finally, once the different INGENIAS models are months and fifteen days. This effort shows an improve- specified, the following process is carried out using the ment in modeling and implementing new applications developed modules in order to obtain the final applica- in terms of productivity. The main reason is that the tion (see Fig. 12): time necessary for coding is reduced because devel- 1. The developer uses the INGENIAS ICARO opers do not need to learn the structure, location and Framework generator module (IIF) to automati- naming rules of ICARO applications files. cally generate code for the design specified with We would like to point out that the presented mod- the IDK tool (see Fig. 12, step 1). IIF generates ules have been validated through their use in the devel- several XML files that describe the behavior of opment of two different applications. The first applica- each agent, java classes for each agent and appli- tion [16] was developed to face the problem of a col- cation, and the XML file describing the applica- lection of robots patrolling around a surveillance envi- tion deployment. ronment. The second application [17] was developed 2. After that, the developer manually inserts code for monitoring and controlling the normal and anoma- into the protected regions of the generated java lous situations that happen when humans access to a classes and implements the new necessary classes specific area. During the development of both appli- (see Fig. 12, step 2). Specifically, the developer cations, the developer only had to write manually the only needs to develop the graphical user inter- body of both the resources methods and semantic ac- faces, knowing how an agent accesses the re- tions along with some auxiliary classes. The remaining sources and how an agent and/or a resource sends code was automatically generated by using as input the an event to an agent to complete the implemen- models created with the IDK. tation of the application. Let us clarify that re- Finally, two challenges constitute our on-going sources code is generated from application enti- work. The first one is related to the validation of the ties specified in the detailed design model using proposal. The developed modules have shown their the INGENIAS modeling language. usefulness and suitability when used in the two afore- 3. The developer uses the ICAROTCodeUploader mentioned projects. They allow to reduce the time nec- module to update the model with the modifica- essary to perform coding tasks and to increase the tions introduced in the protected regions (see Fig. quality of the developed systems since the generated 12, step 3). It enables the developers to always code contains no errors. Although these results are keep synchronized the model and the source very promising, we are currently designing an exper- code, so that changes introduced in the source imental evaluation [12] with developers to determine code are kept when the code is again regenerated the acceptance of this proposal in a close future. The from the model. Finally, the script file generated second challenge is mainly related to the extension of by the IIF module is executed by the deployment the IDK modules to provide additional support. Cur- manager to launch the developed application. rently, we are extending the IIF module to generate the event notification code. 5. Conclusions
This paper has shown the easiness to implement Acknowledgements AmI applications using the IDK tools to design them as MAS. The paper has also described the two de- This work is partially supported by Spanish Minis- veloped to generate code for the ICARO framework terio de Economía y Competitividad / FEDER under from the design. More specifically, the development projects TIN2010-20845-C03-01 and TIN2012-34003 of these two modules (code generator and code up- and TIN2013-47074-C2-1-R. 12 J.M. Gascueña et al. / ICARO in support of AmI
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