Towards ubiquitous tourist service coordination and process integration A collaborative travel agent system architecture with semantic web services

1、towards ubiquitous tourist service coordination and process integration: a collaborative travel agent system architecture with semantic web services dickson k.w. chiu1, yves t.f. yueh2, ho-fung leung 3, and patrick c. k. hung4 1dickson computer systems, 7 victory avenue, kowloon, hong kong (contact)

2、 2department of computer science and engineering, hong kong university of science and technology, hong kong 3department of computer science and engineering, the chinese university of hong kong, hong kong 4faculty of business and information technology, university of ontario institute of technology,

3、canada email: , , .hk, patrick.hunguoit.ca a preliminary version of this paper has been presented at the ieee 21st international conference on advanced information networking and applications (yueh et al. 2007). abstract with the recent advances in internet and mobile t

4、echnologies, there are increasing demands for ubiquitous access to tourist information systems for service coordination and process integration. however, due to disparate tourist information and service resources such as airlines, hotels, tour operators, it is still difficult for tourists to use the

5、m effectively during their trips or even in the planning stage. neither can current tourist portals assist tourists proactively. to overcome this problem, we propose a collaborative travel agent system (ctas) based on a scalable, flexible, and intelligent multi-agent information system (mais) archit

6、ecture for proactive aids to internet and mobile users. we also employ semantic web technologies for effective organization of information resources and service processes. we formulate our mais architecture for ctas further with agent clusters based on a case study of a large service-oriented travel

7、 agency. agent clusters may comprise several types of agents to achieve the goals involved in the major processes of a tourists trip. we show how agents can make use of ontology from the semantic web to help tourists better plan, understand, and specify their requirements collaboratively with the ct

8、as. we further illustrate how this can be successfully implemented with web service technologies to integrate disparate internet tourist resources. to conclude, we discuss and evaluate our approach from different stakeholders perspectives. keywords tourist information system, ubiquitous computing, c

9、ollaborative process integration, multi-agent information system, semantic web services, ontology 1.introduction tourism has become the worlds largest industry and has experienced consistent growth over the recent years. the world tourism organization (2006) predicts that by 2020, tourist arrivals a

10、round the world will increase over 200%. tourism has become a highly competitive business all over the world. competitive advantage is increasingly driven by the advancement of information technology and innovation. currently, the internet is the primary source of tourist destination information for

11、 travelers. with the recent advances in hardware and software technologies, the internet is quickly evolving towards wireless adoption (lin as well as the provision of personalized assistance and automation to the tourists, each having different preferences and support requirements that often being

12、changed during the trip. with the help of ontology, the ctas can help tourists better understand and guide them to specify their needs and preferences collaboratively, so that the appropriate information and services resources could be located from the semantic web (chiu et al. 2005). because scalab

13、ility and flexibility, tourists cannot be flexibly assisted in a centralized manner. the assistance of increasingly powerful mobile devices becomes the enabling technologies. under individuals instructions and preferences, intelligent software agents within ctas can be delegated to help recommend, p

14、lan, and negotiate personalized activities and schedules, thereby augmenting the users decisions collaboratively. as such, we propose a scalable, flexible, and intelligent multi-agent information system (mais) infrastructure for a ctas with agent clusters for tourist service coordination and integra

15、tion. each agent cluster comprises several types of agents to achieve the goals of the major tasks of a tourists trip, such as, information gathering, preference matchmaking, planning, service brokering, commuting, and mobile servicing. the agents also make use of ontology from the semantic web to s

16、earch information and make recommendations to the tourists. further, we detail how this can be effectively implemented with web service and semantic web technologies, integrating disparate internet tourist resources. the remainder of this paper is organized as follows. section 2 introduces backgroun

17、d and related work. section 3 explains an overview of an mais and a development methodology for such a ctas. section 4 details how our mais architecture and implementation framework can meet the tourists needs. section 5 concludes the paper by discussing the applicability of our approach in differen

18、t stakeholders perspectives in collaboration with our plans for further research. 2.background and related work we have not found any similar work on ctas with this holistic approach and the deployment of mais for this purpose. traditionally, travelers often have to manually visit multiple independe

19、nt web sites or use traditional means such as telephone, fax, or even in one-on-one consultation to plan their trips. this requires tourists to register their personal information multiple times, spend hours or days waiting for a response or confirmation, and make multiple payments by credit cards.

20、this could be a tedious and error-prone process, especially when a tourist has a complex plan or wants to search as much information as possible before making a decision. tourists are discouraged with the lack of functionality via traditional ways. they are demanding the ability to create, manage, a

21、nd update itineraries. buhalis and licata (2002) discuss the future of e-tourism intermediaries while rayman- bacchus and molina (2001) predict the business issues and trends of internet-based tourism. however, both groups did not focus on a tourists requirements or a software development perspectiv

22、e. intelligent agents are considered as autonomous entities with abilities to execute tasks independently. he et al. (2003) present a comprehensive survey on agent-mediated e-commerce. an agent should be proactive and subject to personalization, with a high degree of autonomy, assisting the users co

23、llaboration with other information systems. in particular, due to the different limitations on different platforms, users may need different options in agent delegation. prior research studies usually focus on the technical issues in a domain-specific application. for example, lo and kersten (1999)

24、present an integrated negotiation environment by using software agent technologies for supporting negotiators but they did not support their operations on different platforms. the emergence of mais dates back to sycara and zeng (1996), who discuss the issues in the collaboration of multiple intellig

25、ent software agents. in general, an mais provides a platform to bring multiple types of expertise for any decision making (luo et al. 2002). lin et al. (1998) present an mais with four main components: agents, tasks, organizations, and information infrastructure for modeling the order fulfillment pr

26、ocess in a supply chain network. lin and pai (2000) discuss the implementation of mais based on a multi-agent simulation platform called swarm. further, shakshuki et al. (2000) present an mais architecture, in which each agent is autonomous, collaborative, coordinated, intelligent, rational, and abl

27、e to communicate with other agents to fulfill the users needs. choy et al. (2003) propose the use of mobile agents to aid in meeting the critical requirement of universal access in an efficient manner. wegner et al. (1996) present a multi-agent collaboration algorithm using the concepts of belief, d

28、esire, and intention (bdi). fraile et al. (1999) present a negotiation, collaboration, and cooperation model for supporting a team of distributed agents to achieve the goals of assembly tasks. chiu et al. (2003) also propose the use of a three-tier view based methodology for adapting human-agent col

29、laborative systems for multiple mobile platforms. in order to ensure interoperability of mais, standardization on different levels is highly required (gerst 2003). thus, based on all these prior works, our proposed mais framework adapts and coordinates collaborative agents with standardized mobile a

30、nd semantic web technologies for a ctas. researches in mobile workforce management (mwm) motivate this research work. guido et al. (1998) point out some mwm issues and evaluation criteria, but the details are no longer up-to-date because of the fast evolving technologies. jing et al. (2000) prototyp

31、es a system called wham (workflow enhancements for mobility) to support mobile workforce and applications in a collaborative workflow environment, with emphasis on a two-level (central and local) resource management approach. both groups did not consider distributed agent based, flexible multi-platf

32、orm business process interactions, or any collaboration support. there are many similarities in mwm and ctas, such as mobility of the users, disparate information and service resources, and collaborative decision requirements. however, user-to-user collaboration (bafoutsou each carrying out actions

33、based on their own strategies. in this section, we explain our mais infrastructure based on a bdi framework. then, we summarized our methodology for design and analysis of an mais for the ctas. 3.1 mais layered infrastructure for a ctas personal assistance information / service resources planning to

34、urist information system multi-agent information system (mais) bdi agents ontologycollaboration protocol web-based 3-tier implementation architecture figure 1. a layered infrastructure for a ctas figure 1 summarizes our layered infrastructure for a ctas. conventionally, tourism information and servi

35、ces are accessible manually through the web or through traditional means such as telephone, fax, or even in person. this could be a tedious and error-prone process, especially when a tourist has a complex plan or wants to search as much information as possible. furthermore, agents can provide adequa

36、te computerized personal assistance to individual travelers over the web and facilitate the protection of privacy and security (chiu et al. 2004). these agents, acting on behalf of their delegators, collaborate through both wired and wireless internet, forming a dynamic mais over the web. the believ

37、e-desire-intention (bdi) framework is a well-established computational model for deliberative intelligent agents. a bdi agent constantly monitors the changes in the environment and updates its information accordingly. ontology help generate possible goals reflecting a tourists requirements, from whi

38、ch intentions to be pursued are identified and a sequence of actions will be performed to achieve the intentions in consideration of the tourists preferences. bdi agents are proactive by taking initiatives to achieve their goals, yet adaptive by reacting to the changes in the environment in a timely

39、 manner. they can also accumulate experience from previous interactions with the environment and other agents. the bdi model can also solve for acceptable tourist arrangements and even a tour plan by mapping constraints generated to the well-known paradigm of the constraint satisfaction problem (csp

40、)(tsang 1993), where efficient solvers are available. internet applications are generally developed with a three-tier architecture comprising front, application, and data tiers. though the use of three-tier architecture in the agent community is relatively new, it is a well-accepted pattern to provi

41、de flexibility in each tier (chiu et al. 2003) and is absolutely required in the expansion of e- collaboration support. such flexibility is particularly important to the front tier, which often involves the support of different solutions on multiple platforms. in our architecture, users may either i

42、nteract manually with other collaborators or delegate an agent to make decision on behalf of their client. thus, users without agent support can still participate through flexible user interfaces for multiple platforms. as the mais architecture involves a large number of autonomous agents, and each

43、agent has its own architecture-specific features such as strategy to find another agent, query preference, advertisement, etc. (chiu et al. 2005; choy et al. 2003), the problem of such architecture is that locating and collaborating with agents in the agent communities become difficult. in order to

44、interact, agents must first know of each others presence and location in the mais. since the mais is open for agents to enter or leave at anytime, it is impossible for programming the agent under the assumption that they know all of their peers. a possible way is to introduce an agent discovery mech

45、anism for agents to find each other dynamically, say, through directory services. dynamic discovery mechanism requires a language to express the capabilities of services, and the specification of a matching algorithm between service advertisements and service requests that recognizes when a request

46、matches an advertisement. ontologies constitute an essential ingredient for discovery. they provide the means to represent different aspects of agents and the basic mechanisms for the match between agents requests and advertisements. advertisements are descriptions of the services provided by the ag

47、ent and used by the middle agents to identify which agent provides a specified service (garrido et al. 1996; gerst 2003). once the provider is found, the requesting agent still needs to query the provider to obtain a service. we adopt owl (lacy 2005) as a service description language as it provides

48、a semantically based view of web services. this spans from the abstract description to the specification of the service interaction protocol, to the actual messages that it exchanges with other web services or agents. figure 2 shows a typical agent collaboration process in a sequence diagram of the

49、unified modeling language (uml). matchmaker advertises confirm the advertisement return the agent names and services return the answer communication using acl send the result back send the reply get the agent name from the db check if the service provided send the query seeker agentmatchmakerprovide

50、r agent send the result back send the reply get the agent name from the db check if the service provided send the query figure 2. a typical agent collaboration process in mais, knowledge and capabilities are distributed across the agents in a way that no single agent has a complete knowledge of the

51、whole mais; and no single agent can perform all the operations that can be performed by all the other agents. despite their limited knowledge and capabilities, agents are able to ask other agents to perform some actions or to provide information. therefore, the ability to communicate with other agen

52、ts is one of the central collaboration skills of any agent in the mais. the inter-agent communications can be performed by adopting the speech-act theory such as fipa acl. the following example shows such a message: (inform :speaker speaker :receiver listener :content (activity horseracing 05/12/200

53、5 10) ) ontologies provide the tools to interpret the content of the message. for example, the speaker may encode its message using the owl ontology shown in figure 3. as the example shows, ontology, by providing a shared conceptualization of the domain, effectively contributes to agent communicatio

54、n by providing a language and dictionary that can be used to express concepts and statements about the domain of the agents. furthermore, those languages and dictionaries can be standardized and shared by all the agents in the mais. figure 3. an example activity using an owl ontology 3.2 mais analys

55、is and design methodology for a ctas based on the framework of chiu et al. (2005), we adapt the methodology for mwm mais to a ctas in this study. we also advocate the system analysis and design methodology to be carried out in two parts. part 1 deals with the overall architectural design. that is, w

56、e have to analyze the high-level requirements and formulate an overall mais infrastructure for the collaboration and integration aspects required by a ctas. the context of a ctas has been studied partially before and is therefore the focus of this paper. the steps for part 1 are as follows: identify

57、 different categories of services and objectives for the tourists with the help of ontologies. if existing ontologies are inadequate, augment them with the specific concepts required by the ctas. identify different types of process of the tourist that the ctas supports. for each process, identify th

58、e major agent to represent each of the process types and then the interactions among the processes based on the ctas requirements. further identify minor agents that assist the major agents to carry out these functionalities. as a result, clusters of different types of agents (instead of a single mo

59、nolithic pool of agents) constitute the mais. this is required because of the complexity of a ctas. identify the interactions required for the collaboration of each minor agent type. design and define the basic logics for all these agents. identify the (mobile) platforms to be supported and where to

60、 host different types of agents. see if any adaptation is required. only after the successful high-level requirement studies and the design of the overall architecture can we proceed to the next part. part 2 deals with the detail design of agents and the methodology has been preliminarily studied by