Integration of knowledge management systems and business processes using multi-agent systems Mariusz Żytniewski University of Economics in Katowice 1 Maja 50, 40-287 Katowice +48 32 2577277 zyto@ue.katowice.pl ABSTRACT of knowledge management systems shows that agent solutions can support both these approaches. To be successful in an Applications of agents in supporting an organisation’s operations organisation, such systems should constitute synergy of addressed in academic literature largely refer to issues connected organisational, technological and human-focused initiatives and with business processes and management of an organisation tools [17]. In particular, the goals of an organisation, as defined knowledge, which are considered separately. In the first case, by the processes it performs, should have an influence on multi-agent systems are perceived as an element that performs and developed systems of knowledge management, which should automates business processes of an organisation and substitutes its ensure the knowledge necessary to perform these processes, IT systems and users. In the second case, agent solutions are affecting the goals that are implemented and results [11]. As a perceived as tools designed to automate or support the user in the result, knowledge management systems should directly cooperate different stages of the life cycle of the knowledge management with systems designed to support the realization of business system. The research discussed in this paper addresses the aspect processes [9]. This relationship can be seen in figure 1. of integrating both these approaches and refers to the point where both these classes of systems meet. The aim of this paper is to present the concept of an original solution ensuring integration of knowledge management systems and business process handling, which is supported by agent systems. The first part of the paper presents current research in the area of integration of software agents within business processes and the processes of knowledge processing. The second part presents the architecture of a software solution designed to support the modelling of business processes and improve these processes by ensuring the process participants access to organisational knowledge. The third part shows an example of using this architecture. Categories and Subject Descriptors I.3.6 Methodology and Techniques Figure 1. Relationship between knowledge management and H.5.3 Group and Organization Interfaces business processes Sources: [9] As figure 1 shows, knowledge management systems should General Terms support the identification of knowledge needs, gather and store such knowledge and support its sharing within business processes. Human Factors, Verification, Experimentation, Design Additionally, they should support creation of knowledge during performance of processes. Such a definition of tasks results from the fact that knowledge- Keywords based organisations use intellectual capital to manufacture knowledge management, user-agent collaboration, software products and provide services, consciously manage intellectual agents, business process modelling capital and are capable of learning. In other words, knowledge- based organisations are those that adapt their offer and way of 1. INTRODUCTION acting to knowledge gained by reflecting on how they previously acted and that consciously manage knowledge resources they possess. Current research into agent technologies supporting business processes and their use in the context of supporting the building In order to use software agents in organisations, it is necessary to support the integration of both these approaches, which is the look for tools that will support the designing of business subject of this paper. processes taking place in organisations on the one hand, and will support the performance of such processes by providing relevant 2.1 AGENT SUPPORTED BUSINESS knowledge on the other hand. In particular, such solutions should PROCESS support specific stages of the life cycle of the knowledge management system [27],[5]. Modelling of business processes is focused on achieving a Of special importance in the process of building knowledge specific goal by performing defined tasks. Users’ goal and tasks management systems is the aspect of knowledge sharing among constitute a key element defining a business process [3] and are users and the context of its use. Such knowledge should be often mentioned in its definition [25]. When defining business contextual, dependent on the process in which it is used and processes in the context of an organisation, a goal and tasks are specific tasks it supports. For that reason, it is necessary to look at viewed within the scope of actions performed by the participants knowledge management systems from the perspective of Virtual of a process. A goal that is achieved through a process is by Community (VO), in which users share possessed knowledge in a nature complex and requires development of a range of activities virtual community [6]. In such systems, users should share not that have to be defined. These activities, according to the theory only subject and process knowledge, but also meta knowledge on of modelling business processes, should be indivisible and clear. knowledge resources. Thus, it is necessary to build solutions that are at the interface of process-oriented systems and knowledge In the case of an agent-supported process, the goals of a process management systems, which will support their integration and can be treated as the goal of a multi-agent system [26]. In this knowledge sharing among participants. case, we can say that the task of an agent is to substitute activities of the user. However, in the case of atomic tasks, goals of an The aim of this paper is to present the concept of an original agent can be twofold. They can consist in performing a specific solution that ensures integration of knowledge management task (substituting a human being) or supporting his/her actions. systems with business processes handling and is supported by agent systems. The first case refers to the performance of business processes by software agents. Research in this area focuses mainly on The first part of the paper presents current research in the area of decomposition of business processes and their performance by integration of software agents within the processes of knowledge agents [7],[20] and concentrates on modelling multi-agent processing. In particular, it indicates requirements for a solution systems as the performer of the system’s tasks. designed to support business processes and manage knowledge about such processes. The second part presents the architecture of In the second approach, the use of software agents consists in a software solution designed to support the modelling of business providing the user with appropriate knowledge required in the processes and improve these processes by ensuring their context of the goal, process or task in which he/she participates participants access to organisational knowledge. The third part [10]. In both cases, both agents and users have to possess shows an example of using this architecture. knowledge appropriate for the context of their activity that allows them to perform the tasks assigned to them. This knowledge can come from the systems of an organisation knowledge 2. STATE OF ARTS management. This paper will address the issue of creating agent-oriented 2.2 AGENT SUPPORTED KNOWLEDGE solutions that enable integration of knowledge management systems in the area of business processes performed by an MANAGEMENT organisation. Tasks of software agents as part of knowledge management Agent supported business processes systems vary. They refer to specific stages of the life cycle of the knowledge management system. In the context of direct support for business processes, the task of such solutions is to ensure appropriate knowledge to the user or agent acting on his/her Agent supported integration of knowledge behalf in a specific business process. Since the research presented management in business procesees in this paper refers to integration of agent-supported knowledge management systems in business processes, it is necessary to analyse these solution more closely. In his work V. Dignum [4] Agent supported knowledge management presented a threefold division of agent solutions in the area of an organisation knowledge management (table 1). Table 1. Threefold division of agent solutions in the area of an Figure 2. Approaches to using agents in business processes organisation knowledge management supported by knowledge management systems Interface agent, An entity operating in isolation from other conversational software agents, lack of mechanisms for agent communication with agents, orientation towards Figure 2 shows that the subject of using software agents within an communication with a human being, possession organisation requires considering three aspects. The use of agents of a local knowledge database and an artificial as an element supporting business processes, as an element intelligence mechanism. Possible connection with an organisation's IT systems through supporting knowledge management and the use of agents to defined interfaces. will allow them to be directly integrated in business processes and Homogeneous Agents have a mechanism for communication will ensure their constant evaluation in terms of usefulness. multi-agent with other agents (usually an interface), it uses Referring to the issues discussed in point 2.1, it can be said that system certain communication standards and queries the use of such solutions is focused on supporting actions of a (cooperating generation languages, uses other agents' human being. From the perspective of knowledge management, software agents) knowledge database, e.g. interface, is able to they should be perceived as an element supporting knowledge adapt other agents' knowledge for its own needs. dissemination. It operates locally in terms of cooperation with the user. It uses agents of one type. The tasks The use of multi-agent solutions in the third approach largely they perform and their abilities are comparable. refers to using them to support selected actions within an Heterogeneous Entities with various roles, characteristics and organisation. In this approach, multi-agent systems are treated as multi-agent knowledge databases. They are created for the an element that supports knowledge processing in knowledge system purpose of performing various tasks in the management systems and as an element of the architecture of such community in which they reside. Their task is to a system. Such solutions are implemented in an organisation, for cooperate to achieve defined goals. instance, to support software management processes [19], support Source: own work based on [4] Call Centre systems [21], [2] where information systems are used in the process of data search using SQL language or [28] to support a consulting company. While such solutions support The application of the first and second types of agents can be specific elements of the life cycle of the knowledge management examined here in the context of using interface agents and system, their problem orientation makes them narrowly chatterbots as an element supporting the tasks performed by the specialised in the area of supporting a selected area of an user and providing him with appropriate knowledge. The use of organisation's operation and there is no question of their such solutions supporting knowledge management in an integration with other business processes and knowledge organisation largely results from the human nature and problems databases. with human memory which cause the knowledge on certain On the other hand, academic literature includes works addressing processes to be lost and forgotten if such processes are not the aspect of knowledge processing, and [18] points out the regularly repeated [16]. It can be noted that typical knowledge necessity to perceive software agent societies as an element management systems make users' knowledge available in the form supporting knowledge integration in an organisation, showing a of documents and links to specific knowledge resources. Usually possible use of an agent system in the process of integration of IT researchers [13] points out here that the use of various methods of systems in the context of using semantic methods of knowledge information presentation can support and improve cognitive representation [8]. In this case, such a solution is focused on processes. However, quite often, a participant of a business automation of the process of semantic knowledge processing process requires a more complex answer to the problem he/she based on data in relational databases. encountered. For instance, how the process in which he/she participates looks like, how certain documents should be prepared or what certain terms mean. In this case, it is necessary to use 2.3 AGENT SUPPORTED INTEGRATION solutions that support a direct dialogue where specific questions OF KNOWLEDGE MANAGEMENT IN of the user find proper answers [24]. In the case of teaching BUSINESS PROCESS processes, in particular Intelligent Tutoring Systems or Learning Management System [23], the use of chatterbots brings In the area of integration of knowledge management systems and measurable benefits, as such solutions support teaching processes business processes, one can indicate such solutions as [12], which through possessed knowledge, substituting in certain situations an address the problem of integration of common or Business expert in a specific area. In this case, they can be perceived as a Intelligence [22] applications within knowledge management teacher [14] which is designed to achieve the goal of knowledge systems. building [23]. In this situation, a chatterbot allows the user to obtain the answer to the problem he/she encountered. In The concepts mentioned earlier show diversity of both the particular, research in this area shows that in the case of teaching approaches in modelling the functionality of agent systems, processes such solutions are an important element supporting resulting from the specificity of their application. In the context of educational processes by increasing the participants' involvement agent solutions supporting business processes from the in learning [1]. The research into the use of chatterbots presented perspective of an organisation, as presented in point 2.1, an herein shows that they can be used in teaching processes, but from employee or agent participating in a business process should the perspective of the operation of an organisation they are more possess appropriate information and knowledge that will allow difficult to use. First, this results from the changeable nature of him/it to properly perform the task in which he/it participates. business processes, which are subject to frequent changes. In the Additionally, such knowledge should relate to the place and time case of Intelligent Tutoring Systems, the schedule and the of performing a business process. From the perspective of objectives of a teaching process are relatively stable. Another knowledge management systems, the task of software agents is to problem is changeability of knowledge. In the case of an provide the participant with appropriate knowledge, which is organisation and its environment, there are continuous changes in required in the context of the process in which he participates and knowledge that is used, which requires constant updating and the task he performs. assessment of knowledge. In the case of learning process, these In this case, agent supported solutions integrating KM and BPM changes are cyclical. Thus, the use of solutions in the form of should have the following functions: chatterbots within an organisation knowledge management systems is more difficult and requires creation of solutions that  Extending currently used standards for describing business and agent technologies resulted in the development of a system processes to include sources of knowledge that supports the architecture that consists of seven layers (figure 3). performance of users' tasks (in the context of the process, place and time).  Enabling direct integration of organisational knowledge within any business processes taking place in an organisation Layer 1. Users The layer of within the scope of the process in which this knowledge The layer of personalization Layer 2. Knowledge should be used and the task that it supports. management of and portal and chatterbots knowledge communication  Automating processes of assessing the functioning of knowledge management systems in terms of their usefulness portal Layer 3. Business Process The layer of in supporting business processes. management of Layer 4. Agent Evaluation software agents  Generating new organisational knowledge at the interface of Tool society business processes and knowledge management. The layer of Layer 5. Multiagent  Using semantic mechanisms for knowledge description for knowledge System easier integration of possessed knowledge with internal sharing The layer of Layer 6. Ontology organisational knowledge. knowledge Layer 7. Database Layer  Independent operation from used IT solutions and enabling storing integration of any knowledge management systems and a Figure 3. Layers of an agent system for supporting knowledge process-oriented solution. management in an organisation The software solution presented in the next chapter fulfils all the Layer 1 refers to the participant of a business process. It can be a above-mentioned requirements. company's employee, customer, department of an organisation or other software agent. It was assumed in the architecture that the 3. SYSTEM PROPOSITION main reason for such an entity's willingness to participate in processes of an organisation is acquisition of certain knowledge. This however does not result from willingness to learn, but This chapter will present the functional scope and architecture of necessity to perform specific tasks that have been assigned to it. In a solution being built. The system is built based on JAVA this case, the knowledge it has to possess is determined by the language and uses various libraries, including the JADE multi- task in which it participates, and the system of knowledge agent platform, JENA mechanisms for ontology semantic management should provide it with specific tools to support the processing, OWL language for knowledge representation and performance of this task, taking into account the context of the BPMN standard for business process modeling. The subsequent process in which it participates. chapter will present an example of using the architecture for modelling a business process and defining knowledge resources Layer 2 of the system is knowledge portal and interface agents. used in it. The task of this layer is to promote knowledge on processes taking place in an organisation and to use semantic mechanisms in the form of chatterbots. It has been assumed in the architecture developed that both these elements can constitute a part of the 3.1 SYSTEM FUNCJONALITY system for an organisation knowledge management or exist INTRODUCTION outside IT systems of the organisation. For that reason, the solution proposed should support the integration of them both. The aim of the solution developed is to support processes of This layer can be treated as the interface of an organisation describing knowledge resources of organisations as part of knowledge management systems indicated in 2.2. business processes taking place in them. The solution is agent Layer 3 refers to business processes. A frequent problem oriented, as it is possible to define software agents and multi- encountered by users is to locate the knowledge required in the agent systems as knowledge sources for a process. The system processes in which they participate, therefore this layer should itself also has its own multi-agent system, which is used in the support modelling of business processes. Based on analysis of process of analysing gathered knowledge and its codification by notations currently used for specification of business process, the means of semantic mechanisms. This paper will present a author used BPMN, extended by additional artefacts to allow to fragment of its functionality in the area of modelling business identify how agents, knowledge portals and other participants processes in BPMN along with the adopted artefacts extending its impact a process. An advantage of this approach is the fact that functionality and the use of a mechanism for evaluating interface knowledge management systems are linked with an organisation's agents (chatterbot) in performing the user's tasks. business processes. Figure 4 shows an example of a business process modelled in BPMN in an IT system supporting business 3.3 SYSTEM ARCHITECTURE processes of an organisation and its representation in the tool developed. The research into the cooperation of knowledge management systems, systems supporting business processes of organisations Localisation User Task Current resource URI Knowledge resources Chatterbot agent extension BPMN toolbar and process editor Figure 5. Interface of access to knowledge resources Figure 4. Proposal to extend business processes by new knowledge resources This interface presents knowledge resources that can be used in the context of a business process and task performed by the user. The next solution is a tool for evaluating an agent’s usefulness, The architecture of a business process modelled in this way makes which constitutes layer 4 of the architecture developed. This it easier to indicate which information should be made available tool makes it possible to interactively define a template for to users while they perform actions in which they participate. The evaluating the usability of an interface agent and define 4 main artefacts extending the functionality of BPMN as indicated parameters of the operation of an agent: effectiveness, in the figure above have been presented in table 2. performance, satisfaction and knowledge sharing [15]. The use of this tool supports the process of selecting agents for specific tasks Interface agent - designates possible applications of an they are supposed to support and allows the operation of an agent interface agent as an element supporting the to be evaluated (figure 6). performance of a specific task by the user. It allows the user to go into the mode of evaluation of an agent's usefulness and use it to support the user's actions. Evaluation stages Parameters and log A multi-agent system - designates a possible application of a multi-agent system to substitute the user or prepare a specific knowledge resource that will be necessary in the decision making process. Knowledge resource - designates a specific knowledge resource in knowledge portal or the Internet that can be Evaluation screen indicated to the user. It can be a document, web service, URL identifier. Consultant - designates a specific person who has the relevant knowledge about the performance of this task. The process of selecting a person to perform specific tasks has been presented in paper [28]. Figure 6. System for evaluating the process of assessing an agent’s usability Table 2. Applied artefacts extending BPMN As shown in point 2.2, interface agents, in particular chatterbots, The use of such artefacts makes it possible to contextually connect can be an element of dissemination of the organisational knowledge resources of an organisation within a specific process knowledge. However, their use in the context of knowledge and task. This shortens the time it takes for users to acquire new sharing should be subject to evaluation, due to changeability of knowledge, because described knowledge resources become business processes and possible obsolescence of an agent's available to each participant of a business process that performs a knowledge. The solution proposed enables analysis of any specific task. The addition of a new knowledge resource by the chatterbot agent published in the Internet. During evaluation of an user is recorded in the system and made available to users agent, the user is informed on an ongoing basis about, among performing the same process and a specific task. This supports other things, which task the agent should support, how long cooperation between users, as each of them becomes the creator conversation lasts and how many questions the user has already and receiver of the system knowledge. asked. Then, the user is asked to complete a satisfaction survey Figure 5 presents an interface of access to knowledge resources of concerning the conversation. Based on that, the system calculates a knowledge management system in the context of the process and the agent's usability indicators for a specific task in which it was task shown in figure 4. used [15]. This is important, as it may turn out that despite its broad knowledge the agent doesn't support appropriately specific tasks. In such a case, it would be necessary to update its knowledge database. Also, its knowledge may become obsolete. Mechanism defined in this way make it is possible to identify such situations. Layer 5 of the tool developed is the layer of a multi-agent system. In the architecture designed, it is perceived as a tool for evaluating knowledge acquired in the process of using the method indicated above and as a tool to build a multi-agent system, substituting the user in accordance with the developed methodology focused on business processes. For implementation of this layer, JADE platform was chosen and a set of agents supporting the process of knowledge evaluation and codification was prepared (figure 7). Figure 8. Part of prepared OWL ontology (main concepts) This layer enables semantic coding of the knowledge of the system proposed and its processing by means of SPARQL queries. The use of this layer contributes to propagation of possessed organisational knowledge and is consistent with the concept of WEB 3.0. It also contributes to propagation of knowledge about an organisation and processes taking place in it, and use of this knowledge by a multi-agent system in the process of analysing Figure 7. Elements of a multi-agent platform organisational knowledge. The architecture developed includes: The last layer 7 is the most technical and refers to the applied system for database management which enables integration of data from any source and its processing.  BootAgent - agent responsible for activating the multi- agent system. Its task is to create agents and activate 4. EXAMPLE OF APPLICATION agent instances of the individual users of the system.  KnowledgeAuditAgent - agent responsible for the The system architecture developed is designed to support business process of analysing the knowledge of the system. It processes, therefore its central module is the module of designing generates usability indicators for the different business processes in BPMN notation. Such a process may come knowledge resources. from other IT systems existing in an organisation or may be  OWLRepositoryAgent - agent responsible for the prepared based on a established model. The example shows a process of maintaining the knowledge database of the process of obtaining a planning permission. When applying for a platform. planning permission in Poland, it is necessary to collect a range of documents. This process is presented in figure 9.  SPARQLRepositoryAgent - agent handling SPARQL database of queries concerning the knowledge database of the platform.  UserAgentXXX – instance of a user agent generated during the operation of the platform. Layer 6 of the architecture being developed is the ontology layer. It is used as an element of semantic specification of the terms used by agents and enables description of knowledge resources in an organisation. The elements of the ontology are presented in figure 8. Figure 9. Process of obtaining a planning permission. While the process of collecting documents itself is widely known, such documents and their content may vary across different places in Poland where they are prepared. Also places of their storage will vary. Therefore, the process illustrated in figure x, though correct for a specific person, is general and for reference only. The application of the solution proposed makes it possible to extend this process by the context of its use including place and time and knowledge resources that can be used, which is BEGIN presented in figure 10. // connect OWL instances for each LOCALISATION(l) for each PROCESS(x) for each TASK(y) for each AGENT(a) if hasTask(x,y) AND hasAgent(y,a) AND hasLocalisation(y,l) GET x and ADD to set A end if end for end for end for end for // set agent performance in connected process,task and localisation for each A(x) for each EVALUATION(e) if hasEvaluation(x,e) i:=i+1; p:=p+e.performance; x.performance := p/i end if end for Figure 10. Extended process of obtaining a planning permission. end for END As a result, the person performing such a process may become equipped with additional knowledge on its course and the source Figure 12. The algorithm of the process of analysing the agent's of this knowledge. He/she also has access to relevant documents usability based on OWL concepts (performance parameter) that have to be completed. In the example above, it has been diagnosed that in the city of Gdynia there is an interface agent published on the website Based on that, the system enables calculation of the agent's http://www.gdynia.pl/, whose task is to support users’ actions. By usability in the context of the task that it supports, place and time means of the interface created, it is possible to evaluate it in the of its performance (figure 13). The user may also use other context of place, time and process. As a result, the user getting knowledge resources that have been assigned to a given process. access to the process may decide based on the agent's usefulness indicators whe ther to use it or not. Agent usability indicators Figure 11. Chetterbot evaluation process on www.gdynia.pl portal Figure 13. Preview of agent usability Based on the interface of evaluating an agent's knowledge(figure 11), the multi-agent system prepares evaluation of its usefulness in this task, which is included as an element of description of a And assign new knowledge resources to the process (figure 14), business process. The algorithm of the process of analysing the agent's usefulness is as follows (figure 12). 6. ACKNOWLEDGMENTS The project was financed from the funds of National Science Centre 2011/03/D/HS4/00782. 7. REFERENCES [1] Benotti, L.,Martínez, M. C., Schapachnik, F. 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