Subject-Oriented Modeling and Execution of Multi-Agent Business Processes Albert Fleischmann∗ , Udo Kannengiesser∗ , Werner Schmidt† and Christian Stary‡ ∗ Metasonic AG Pfaffenhofen, Germany Email:
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[email protected] † Technische Hochschule Ingolstadt, Germany Email:
[email protected] ‡ Johannes Kepler University, Linz, Austria Email:
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Abstract—This paper addresses a gap in handling multiagent business processes that has prevented their largerscale adoption in practice: the lack of a conceptual modeling approach that is easily understandable by business domain experts and sufficiently formal for direct transformation into executable systems. The emerging paradigm of subject-oriented business process management (S-BPM), which has been evaluated through academic research and is increasingly deployed in commercial applications, has the potential to augment multiagent system (MAS) models with a process-centric layer that preserves autonomy and concurrent interaction of agents as essential system characteristics. In this paper we provide an aligned meta-model and illustrate its operational benefits with examples from business process applications. Keywords-Agent-based Business Process Management, Subject-oriented Business Process Management (S-BPM), Multi-Agent Systems
I. I NTRODUCTION Many process management applications in business and engineering exhibit the characteristics of a complex, dynamic system whose behaviors emerge from the interaction of distributed, autonomous entities. Such a view of process management is most closely matched by the agent-oriented paradigm [1]. Among the benefits of using agents in process management are higher adaptability, extensibility and robustness when compared to traditional approaches that rely on pre-defined, centralized control flows. A few examples of agent-based process management systems have been developed demonstrating these features, among them systems for customer quote services [2], production control [3], and supply chain management [4]. Despite the extensive work on agent-based systems also including process applications, the adoption of research results by industry has generally been poor [5]. One of the reasons identified has been the high specificity of most agent-based methodologies [6]. A few researchers therefore propose to tie agent-based approaches closer to existing software engineering methodologies such as UML [7]. Other efforts aim at integrating agent-based modeling frameworks with business process modeling techniques
such as Petri Nets and BPMN [8] [9]. Hereby, the lack of an explicit business process perspective becomes evident in agent-based modeling. However, intelligible models are required to enhance understanding by business users as they ”tend to think in terms of processes and business entities” [8]. To that respect, a number of problems in mainstream business process modeling exists. They are related to handling unforeseen events, concurrent interaction and (lack of) execution semantics - the lack of humancentered representations of multi-agent system capabilities remains a major obstacle for bringing multi-agent process technologies to business practice. Subject-oriented Business Process Management (S-BPM) [10] includes an overarching approach to modeling and execution that already has turned out supportive in a number of commercial process applications. Unlike traditional workflow approaches based on centralized control flow, S-BPM emphasises the ”subjects” in a process, in terms of decentralized, interacting entities that encapsulate their individual behaviors. It provides a substantial means to overcome intelligibility problems of complex, decentralized processes, as well as formal semantics that allow direct transformation into executable multi-agent systems. The process applications in which S-BPM has been applied to date involve only human agents. In this paper we will show that subject-oriented models and their capability to structure execution support can be applied independently of the particular agents (including human and computational) executing the process. By focussing on software agents as the subjects in a process, we hope to present a vehicle for greater industry uptake of agent-based process applications. Central to a subject-oriented view of multi-agent systems is the conceptual relationship between agents and subjects: Agents ”embody” instances of subjects in a specific context. The separation of agents and subjects provides benefits in terms of design and execution variability. The paper is structured as follows: Section II reviews existing conceptual models of multi-agent business processes and highlights their shortcomings. Section III introduces the basic concept of S-BPM. Section IV
proposes a combined meta-model that brings together the core concepts of the Agent/Group/Role (AGR) model [11] and the process modeling constructs of S-BPM. The meta-model facilitates understanding of the conceptual relationship between subjects and agents, and of the benefits resulting from separating the two notions including greater variability in design and execution. Section V concludes with a discussion of achievements and further research. II. E XISTING C ONCEPTUAL M ODELING A PPROACHES FOR M ULTI -AGENT S YSTEMS A number of conceptual models have been proposed in the MAS literature, abstracting from specific platforms and programming languages [12]. A set of core elements of MAS have been proposed in the Agent/Group/Role (AGR) model [11], shown in Fig. 1. An agent is defined as ”an active, communicating entity playing roles within groups”, where a group is ”a set of agents sharing some common characteristic” (e.g. an organizational unit) and a role is ”the abstract representation of a functional position of an agent in a group”.
Figure 1.
[9] that today is the most commonly used business process modeling standard. Yet, there are major problems related to the use of BPMN due to ill-defined execution semantics and a lack of flexibility in terms of resource management, exception handling and process variation, among others [16]. Most of these problems are caused by the emphasis that BPMN (and similar approaches) places on centralized control flow - a paradigm that is at odds with the notion of autonomous agency [1]. III. S UBJECT-O RIENTED B USINESS P ROCESS M ANAGEMENT A. Origins and Applications Subject-oriented Business Process Management (S-BPM) [10] was first proposed by Albert Fleischmann in 1994 [17]. It is inspired by various process algebras (see e.g. [18], [19], [20]), by the basic structure of nearly all natural languages and by the systemic sociology developed by Niklas Luhmann [21]. In the active voice of many natural languages a complete sentence consists of three basic components: subject, predicate and object. The subject represents the active element, the predicate the action and the object is the entity on which the action is executed. According to the organisational theory developed by Luhmann, the smallest organisation consists of communication executed between at least two information processing entities [21]. Fig. 2 summarizes the different origins of S-BPM.
The Agent/Group/Role (AGR) model
The three core elements in the AGR model can be found in many other MAS models, although some definitions and levels of detail vary across the models [13]. The notion of a role, in particular, is commonly seen as central in the development of MAS for distributed, cooperative problem solving [14]. Further organizational metaphors have been added to MAS models such as organizational structure and organizational rules [15]. They aim to reduce the conceptual distance between MAS and human organizations, thus fostering their deployment in realworld business and engineering applications. Greater ease of engineering MAS for business processes and other applications has been the driver for the development of modeling languages as extensions of established industry standards. An example is AUML [7] that is an agentoriented extension of the widely-used UML standard in software engineering. Recently a number of researchers have recognized the need to describe multi-agent business processes in a language that can be easily understood by business people. Not surprisingly, many approaches have been proposed based on the Business Process Model and Notation (BPMN) [8]
Figure 2.
Origins of S-BPM
The subject-oriented modeling approach fits with the formal semantics of an abstract state machine [25], which allows automatically converting S-BPM models into executable code. The S-BPM approach has been evaluated in many academic and industrial projects, documented in various publications. We briefly mention some of them, representing S-BPM use cases in organisations varying in size from 500 up to a hundred thousand employees: FI-TS, an IT service provider with around 500 employees in the banking area, specified its service order and delivery process
in S-BPM [22]. NEC developed a detailed methodology for BPM based on S-BPM which allows to manage the development and maintenance of very complex processes in huge companies [23]. Swiss Telecom has implemented several processes with S-BPM. One example is an incident management process that is used by several partners of Swiss Telecom. In [24] the implementation of a process for ordering iPhones is described. S-BPM is also in the evaluation phase in several automotive manufacturing companies in Germany. Tool support for generating, validating and executing subject-oriented process models is provided by a commercial vendor (www.metasonic.de/en).
Figure 3.
Symbols used in subject-oriented process descriptions
B. Basic Concepts Subjects are the main building blocks in S-BPM. Business processes are viewed as emerging from both the interaction between these subjects and the local behaviors encapsulated within the individual subjects. Subjects operate in parallel and can exchange messages asynchronously or synchronously. This view of processes as the results of autonomous, concurrent behaviors of distributed entities fundamentally differs from traditional approaches that are based on global control flow. At the same time, it is closely connected to an agent-based view of the world. A subject is a behavioral role assumed by an ”actor”; i.e. an entity that is capable of performing actions. The entity can be a human, a piece of software, a machine (e.g., a robot), a device (e.g., a sensor), or a combination of these. This is consistent with the notion of an agent; for example, in [13] an agent is defined as ”an entity that performs a specific activity in an environment of which it is aware and that can respond to changes”. The relationship between agents and subjects will be described in more detail in section IV. Subjects can execute local actions that do not involve interacting with other subjects (e.g., calculating a price and storing a postal address), and communicative actions that are concerned with exchanging messages between subjects, i.e. sending and receiving messages. The two types of actions are consistent with similar distinctions in MAS research. For example, in the Gaia methodology [15] local actions are called ”activities” and communicative actions are called ”protocols”. Subjects are one of five core symbols used in S-BPM, as shown in the glossary in Fig. 3. Based on these symbols, two types of diagrams can be produced to conjointly represent a process: Subject Interaction Diagrams (SIDs) and Subject Behavior Diagrams (SBDs). SIDs provide a global view of the process, including the subjects involved and the messages they exchange. The SID of a simple ordering process is shown in Fig. 4. Subject Behavior Diagrams (SBDs) provide a local view of the process from the perspective of individual subjects. They include sequences of states representing local actions (called ”function states”) and communicative actions in-
Figure 4. Subject Interaction Diagram (SID) of an order handling process
cluding sending messages (called ”send states”) and receiving messages (called ”receive states”). State transitions are represented as arrows, with labels indicating the outcome of the preceeding state. Fig. 5 shows the SBDs of the subjects ”Customer” and ”Order handling”. The two curved arrows in the figure are not part of the S-BPM notation; we inserted them to highlight how the two subject behaviors are interconnected through respective ”send” and ”receive” actions. A precise and complete definition of the semantics of all S-BPM modeling elements can be found in [10].
Figure 5. Subject Behavior Diagrams (SBDs) of ”Customer” and ”Order handling” subjects
C. Asynchronous Interaction One of the key features of S-BPM is its support for asynchronous interaction between subjects. It is based on the input pool concept that can be viewed as a mailbox for receiving messages. It can be illustrated using the SBD for the subject ”Customer” in Fig. 5. When this subject is in the receive state ”Wait for confirmation”, it can access its input pool and check for messages. As long as there is no message in the input pool, the subject remains in the receive state. When the message ”order confirmation” arrives (from ”Order handling”), the subject ”Customer” removes that message from the input pool and follows the transition to the next function state defined in the SBD. The input pool can be structured according to behavior options: The modeler can define how many messages of which type and/or from which sender can be deposited and what the reaction is if these restrictions are violated. This means the type of synchronisation during message exchange can be individually specified. The input pool concept is not available in traditional, control-flow based approaches such as BPMN. As a result, S-BPM has a unique position in that it supports asynchronous in addition to synchronous interaction. D. Integration of Data Most workflow approaches neglect the representation of data within the control flow [16]. S-BPM has more powerful mechanisms for representing data structures, access rights and the flow of data. Messages transport data from the sending to the receiving subject, and internal functions operate on the data. Fig. 6 shows the connection between the behavior of a subject and the data in more detail, using a part of the SBD of the subject ”Customer” as an example. Here the internal function state ”Prepare order” uses local data to generate new data to be conveyed as the payload of the ”order” message.
Data objects can be of physical or logical nature, e.g., a paper form or a set of data in a computer system. Depending on the type of data, the actions operating on it are realised differently. For example, adding a name to a data object can be realized by filling out a paper form or by completing a software user interface. Today in nearly all cases objects and the related actions are based on IT systems. This means the internal functions of a subject behavior are realized as methods of a data object or implemented as a service in a service-oriented architecture. These data objects have an additional method for each message. If a message is sent the method allows receiving the values of its sent data, and in case a message is received the corresponding method is used to store the received data in the object. Since objects are essential for doing business they are termed business objects. E. Non-Deterministic Behavior Subject-oriented models can describe any complex behavioral pattern, including conditional and parallel branching, loops and exception handling. For space reasons, we show in this paper only how exceptions (i.e., known but unpredictable events) are handled - an important feature for agentbased business processes where non-deterministic behavior may frequently occur. In our order management example let us assume that a customer wants to change an order after it has been sent. Fig. 7 shows an extended SID that now contains the message ”change order” in the communication structure. It also includes two possible replies from order handling: a message ”order change accepted” and a message ”order change rejected”.
Figure 7. Modified Subject Interaction Diagram (SID) to include messages dealing with order changes
Figure 6.
Subjects and business objects
This unpredictable event also affects the behavior of the involved subjects. Due to the lack of space in this paper, we describe only the modified SBD of the subject ”Order handling”, shown in Fig. 8. The flags in all states following receipt of the original order indicate that in all of these states the message ”change order” is accepted. If this message arrives during one of these states, the subject behavior ”jumps” into the state ”Check order” in the middle of Fig. 8. Here, the order is checked and then the message ”order change accepted” is sent to the customer and the behavior execution continues to the state ”Handover to shipment”. If, on the other hand, the message ”change order” arrives in a state following ”Handover to shipment” of the original order,
the message ”Order change rejected” is sent to the customer, as specified on the righthand side of Fig. 8. After sending back the rejection message the subject behavior is continued from where it had been interrupted by the message ”change order”.
Figure 9.
Figure 8. The behavior of the subject ”Order handling”, modified to handle order changes
IV. AGENTS AND S UBJECTS The subject-oriented method can be used for modeling and executing multi-agent business processes. Fig. 9 shows a meta-model combining subject-oriented modeling concepts with the core elements of the AGR meta-model introduced earlier (Fig. 1). We chose the AGR meta-model because it is simple but sufficient for representing the connection between subject-oriented and agent-based models, but in principle any MAS meta-model may be used. Cardinalities have been omitted in Fig. 9 for presentational clarity; all relationships are assumed to be many-to-many. According to the meta-model, a set of subjects compose a business process. Subjects execute actions, captured as predicates, operating on objects. Here the term predicate is used in a naturallanguage sense; i.e. that part in an active voice sentence that denotes an action. Subjects can execute three different types of actions: Sending messages to other subjects, receiving messages from other subjects and performing local actions on business objects. Business objects are transported via messages from the sending subject to the receiving subject. Local actions executed on a business object, such as creating, deleting or changing the object, can be seen as method invocations known from object-oriented software development. In a multi-agent system, agents can be involved in several processes, where the same agent can embody different subjects across different processes. (We use the term ”to embody” in its colloquial sense as ”to give a concrete form to”, not in an AI sense.) In turn, the same subject can be embodied by a single agent in one process or by a group of agents in another process. Roles are generalized
Meta-model of S-BPM combined with the AGR model
combinations of subjects from different processes, cast into functional positions within the agent organization. Roles are assigned to specific agents that execute the actions defined in subject descriptions [26]. Agents can be people, software programs, robots etc.; as a result, subjects may be embodied by heterogenous groups consisting of a mixture of different agent types. For instance, an ”Order handling” subject may be embodied by a group of two interacting agents: a software controlling the order handling workflow, and a human user entering required data. Subjects can be viewed as ”process-related” roles, clearly distinct from the organizational role concept in MAS. They fit with the notion of ”preliminary roles” in the Gaia methodology that ”remain the same independently of the actual organizational structure” [27]. Subject-oriented process models can be understood as an abstraction layer that allows varying the particular implementation and execution of a process by multi-agent systems, thus allowing for more flexibility at design time and at runtime. A. Variability of System Design The implication of separating subjects from roles and agents is that the same process model can be implemented using different organizational structures, agents and agent environments. In turn, the same agents and agent structures can implement different process models. Take the example shown in Fig. 10. It includes two processes: the ordering process, and a vacation application process. The subjects ”Order Handling” and ”Employee” are associated with the group ”Order Dept.” via the role ”Order handler”, and the subjects ”Employee” and ”Shipment” are associated with the group ”Warehouse Dept.” via the role ”Warehouse worker”. As a result, any of the agents ”Florian” and ”Katrin” can embody instances of the subjects ”Order Handling” and ”Employee”, and any of the agents ”Josef”, ”Christian” and ”Thomas” can embody instances of the subjects ”Shipment” and ”Employee”. The subject ”Enterprise Resource Planning” is associated with the
role ”ERP System” that is directly connected to the agent ”SAP”. Constraints can be added at design time to restrict the number or type of agents that are allowed to embody a specific subject. In S-BPM these constraints are called business rules; they support embedding process models in a particular domain context. In the example shown in Fig. 10 there might exist the rule that instances of the subject ”shipment” must be embodied by agent ”Josef” for a specific type of customer (e.g. ”Gold” customers).
Figure 11.
Figure 10. Flexible mapping of subjects to agents (and groups of agents) via roles
Implementation of subject-oriented processes
A more detailed discussion about the relationship between subject-oriented processes and organizational and implementation aspects can be found in [10] and [28]. Commercial tool support (www.metasonic.de) already exists for implementing subject-oriented process models in human agent organizations. A number of agent-based frameworks provide similar features for computational multi-agent systems. A research issue is the combination of tools for implementing hybrid systems consisting of human and computational agents. The subject-oriented approach has recently been proposed as a basis for seamlessly integrating automated production control with enterprise-level business processes [29] [30] [31]. Prototype implementations of subject-oriented production processes based on human and computational agents are being developed within the ”Subject-Orientation for PeopleCentred Production” (SO-PC-Pro) project funded by the European Union. B. Variability of Execution
Agents that embody the subjects in a process model may be human, computational or a mixture of both. The choice of agents strongly influences the systems and capabilities needed to implement a process model. Fig. 11 shows an implementation framework of a subject-oriented workflow system with links to agents (human or computational) and other IT systems. The numbers in the figure indicate different aspects of implementation: 1) Subject behavior, including sending and receiving messages (1a) and calling methods on business objects (1b) 2) Business objects, in terms of data structures with methods or services allowing for reading and writing data (see Section III-A) 3) Interfaces for agents, including front ends for human agents and application interfaces for computational agents (agent layer) 4) Data stores (persistence layer)
When subject-oriented process models are executed, instances of subjects are created. Subject instances can be mapped dynamically (i.e. at runtime) to specific agents. As a result, the same agent can embody multiple subject instances concurrently, and multiple subject instances can be spawned based on the same process model. Fig. 12 shows this variability of execution using the ordering process as an example. It also shows three triggers for creating process instances (or subject instances): business rules, messages, and black-box behavior. Business rules can be defined to trigger the creation of process instances based on specific temporal events and/or states of specific data items. For example, the ordering process may be created by the customer at regular time intervals or when a minimum stock level has been reached. The business rules may be implemented in a conventional workflow execution system or in a computational agent. Messages can trigger the creation of subject instances as
Figure 12.
Instances of processes
a response to interactions with other subject instances. In the ordering example, an instance of the subject ”Order handling” is created when the message ”order” is received from the subject instance ”Customer”. Receiving this message requires an action that is concerned with reading the ”order” message and removing it from the input pool of the ”Order handling” subject. This action can be performed by any agent that is connected to ”Order handling” via role assignment. Additional mechanisms may be defined to restrict access to the input pool, such as sender characteristics (e.g., the ”Gold” customer mentioned earlier) and maximum number of messages. These mechanisms can be defined depending on the specific agent environment and possible requirements for asynchronous and synchronous communication. Once a specific agent chooses to execute the ”receive” action, an ”Order handling” subject instance is created. Black-box behavior captures all those examples of autonomous, pro-active behavior that cannot be described using pre-defined business rules or as reactions to incoming messages. In the ordering process example, a subject instance of ”Customer” may be created whenever an agent assigned to the corresponding subject chooses to create an order, not necessarily driven by any stock policies. This could be the case when the agent changes its expectations of the future consumption, availability or cost of ordered products. Such expectations are encapsulated in the agent, not visible or predictable for external observers or even system designers. The subject-oriented approach allows agents to choose whether or not to instantiate some of the subjects in a process. These subjects are marked as ”start subjects” in the process model, using a solid circle in the top right corner of the first state specified in their SBD (shown in Fig. 5).
Agent/Group/Role model, improving the intelligibility of the encoded business logic and increasing variability by introducing an additional abstraction layer. The decoupling of business logic from system design frees business domain experts from having to understand and deal with complex implementation issues. In turn, MAS designers are provided with a high-level yet formal specification of the process to be supported by a multi-agent system. This provides a basis for addressing an important concern in the development of multi-agent business processes: the ”difficult[y] to ensure that process-wide constraints are satisfied” [1]. Further work is needed to expand S-BPM as a complete specification language for the business requirements of multi-agent processes. This would require additional modeling elements representing non-functional process requirements. The variability at runtime that results from the subjectoriented approach is based on preserving the autonomous behavior of agents within the constraints of the business logic. Unlike common workflow approaches based on centralised control, this allows exploiting the key features of agentbased business process systems: flexibility, extensibility and robustness. Given that mainstream BPM approaches fail to meet the needs for more flexibility in practical business applications, the subject-oriented approach has the potential to become a catalyst for greater adoption of multi-agent business processes in industry. R EFERENCES [1] N.R. Jennings, T.J. Norman, P. Faratin, P. OBrien, B. Odgers, Autonomous Agents for Business Process Management, Applied Artificial Intelligence, Vol. 14, 2000, pp. 145-189. [2] N.R. Jennings, P. Faratin, T.J. Norman, P. OBrien, B. Odgers, J.L. Alty, Implementing a Business Process Management System Using ADEPT: A Real-World Case Study, Applied Artificial Intelligence, Vol. 14, 2000, pp. 421-463. [3] S. Bussmann, N.R. Jennings, M.J. Wooldridge, Multiagent Systems for Manufacturing Control. A Design Methodology, Springer Series on Agent Technology, Springer, 2004. [4] J. Nirupam, S. Rajagopalan, I. Karimi, Agent-based supply chain management*/1: framework, Computers and Chemical Engineering 26 (2002), pp. 1755-1769. [5] D. Weyns, A. Helleboogh, T. Holvoet, How to Get MultiAgent Systems Accepted in Industry?, International Journal of Agent-Oriented Software Engineering, Vol. 3, 2009, pp. 383390.
V. C ONCLUSION
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