Planning algorithms could provide hidden but essential functions for the NII. They could enable development of software robots that use planning technology to consult repositories of programs, protocols, and indices and construct plans to satisfy users’ requests for information or services. As a result, users would not have to concern themselves with new programs, archives, and protocols as they become available. Instead, they could specify what they want, and leave to planning algorithms the determination of how to achieve the goals. By exploiting planning technology, intelligent software agents could serve as user advocates and make the best use of available resources.
3.3.2 State of the Art
Successful planning systems have been developed for several tasks, including factory automation, military transportation scheduling, and medical treatment planning. Researchers interested in NII applications are beginning to develop software agents that take information-gathering goals supplied by users and then plan and execute actions to achieve these goals. The generation of plans of action for using NII services is a special case of automatic programming in which the programs (plans) involve loops and conditional branches, with primitive statements couched in terms of basic commands to local and remote networking and database servers. Although early planning systems could only generate straight-line programs, recent work has extended the plan language to include conditionals (for example, if the NCSA site is available, then get the file there, otherwise get it from CERN), and prototype planners are being developed to automatically synthesize loops (for example, repeatedly attempt to access this server on one minute intervals until successful). Current planners can handle the expressive goal languages that will be demanded by NII applications--least-commitment planning algorithms can satisfy goals that are composed using disjunction, negation, and nested quantification. To date, most planning research assumes complete information; this restriction is a definite obstacle to the application of planning technology to NII domains where incomplete information is the norm. The research community has recognized this challenge; several recent planning systems include principled techniques for coping with uncertainty and sensing actions.
3.3.3 Research Opportunities
The NII offers a perfect target for modern planning theory. First, the critical information required for decision making is readily available in symbolic form from electronic sources, thereby eliminating or reducing many of the difficult interpretation problems encountered in planning in areas like robotics. Second, the actions involve computer programs with well-understood semantics and input-output behavior that is easily observed and interpreted by other computer programs. Finally, NII-related problems encourage the use of predictive models, involve manageable levels of uncertainty, and are characterized by clear performance criteria.
Planning systems for the NII will have to cope with uncertainty regarding the availability of services. They will have to make plans with radically incomplete and possibly out-of-date information. Planning systems will need to cope with the tradeoffs between the benefit of computing the best possible plan and the need to act quickly--before all avenues have been explored. Similarly, NII planning systems must balance the benefit accrued from high-quality information sources with the cost of invoking premium databases. Although modern planning algorithms can handle expressive action representation languages that are capable of representing the rich variety of Internet utilities and NII services, combinatorial problems might prevent such algorithms from scaling to handle large problems. To combat this difficulty, research is needed on search-control languages and domain compilation techniques.
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