To combat this difficulty, research is needed on search-control languages and domain compilation techniques. It will connect people to people, and help them with their jobs and tasks. For example, a photograph of Bill Clinton standing in front of the White House with Al Gore is indeed a picture of Bill Clinton. It is necessary to integrate in ITS (Intelligent Tutoring System) analysis mechanisms and reactions to simulate or overcome natural tutoring environment achievements. However, the full realization of this promise requires a concerted attack on a variety of fundamental scientific problems. An effective and efficient integration of all the key capabilities is still a long-term project. For example, people can use a freeway signpost that reads "I-95 New England" to get to Boston because they know that I-95 is the name of a freeway, the sign means I-95 goes to New England from here, and Boston is in New England. We discuss these challenges briefly here; in Section 2 we elaborate and explain the potential role of intelligent software systems in meeting these challenges. Human identification using various biometric modalities (e.g. Most information currently stored on the Internet uses one of two degenerate knowledge representation methods: databases or natural language text. Edited by Daniel S. Weld, University of Washington, Editors: Joe Marks, Mitsubishi Electric Research Laboratories Daniel G. Bobrow, Xerox Palo Alto Research Center. It must adjust automatically to the needs and idiosyncrasies of individual users, and it must change as the user’s experiences or requirements change. The problem of comprehensible access will only worsen with the widespread deployment of digital libraries and commercial transactions; it could become an insurmountable barrier for new users. The investigation of incremental approaches to integration--in which initially small subsets of prototype capabilities are combined and applied, and then both the number of capabilities and the quality of the resulting behavior are gradually improved and applied in a wider range of domains--is one promising means of addressing this latter need. These possibilities suggest that the majority of network interactions will eventually be between programs. Previous Page. This report recommends support of AI research in eight key areas, each of which has substantial promise for high payback to the NII effort. To evaluate a prototype software system (Subsection 2.3.1), a designer must be able to simulate at least part of the environment in which the system is to operate. Users should be able to phrase requests in terms of what they want accomplished and leave the problem of determining how to achieve that goal to the interface. In general, current computer-vision techniques are capable of impressive feats under controlled conditions, but these techniques often prove to be brittle and nonrobust under real-world conditions. A sampling of tasks such agents could perform illustrates the promise and challenge of multiagent coordination and collaboration. Research in knowledge representation (Subsection 3.1) seeks to discover expressive and efficient methods for representing information about all aspects of the world. The intelligence in the network could be embedded at any layer of the network based on the application requirements. Research on software agent architecture will enable more sophisticated interfaces, software development aids, and simulation systems. Although the majority of human knowledge remains stored in paper documents, document analysis and recognition will be needed to convert scanned text and illustrations into symbolic form, thereby facilitating data and knowledge management services. Then, we outline specific research areas with potentially large payback. The polynomial-time inference and classification schemes of knowledge representation (Subsection 3.1) provide the desired functions, but multiple taxonomies must be supported, and classification schemes must allow evolution over time. Firstly a set of condition monitoring sensors developed by the partners of the consortium which monitor appropriate parameters. Agents should be goal oriented, allowing users to state what they want accomplished, then automatically determining how and when to achieve the goal. In addition, the opportunities for machine-learning applications in the NII suggest specific research directions. An intelligent agent cannot possibly have complete and timely information about Internet, diagnosing problems with human or complex nonhuman systems is inexact and characterized by noisy and conflicting information, and manufacturing and logistical control problems are fraught with uncertainty. The architecture of an agent is the computational structure that, along with the more dynamic knowledge represented within it, generates the agent’s behavior in the environment. Constructing, maintaining, and extending the National Challenge applications and other complex systems poses many hard problems apart from the issues of prototyping, specification, and reuse just discussed. An information seeker contacts an appropriate local broker and its request is passed along until it is fulfilled. Managing large-scale projects requires facilities for coordinating independent activities with groupware and managing the project plans themselves. Because determining which duties must be paid requires reasoning about the type of merchandise, the scope of services provided, and the relevance of tax codes, AI techniques can provide significant assistance in meeting the challenges of integration and translation. The NII will be orders of magnitude more complex than the Internet, and could easily become a labyrinth of databases and services. A centralized index can be seen as the degenerate case of this distributed scheme, but the existence of multiple, competing brokers could provide faster response time, improved specificity, and better adaptation to change in primary sources. Research in several areas is needed to enable agents to tailor explanations to individual users (e.g. Replacing HR. Codified semantic information, however, can be processed by automated agents (as well as a manual browser). More work of this kind is needed to extract the best possible performance from known techniques. Making an articulated figure move in a visually plausible way or designing a solid model of a manmade artifact are difficult. Informational graphics, which are mostly two-dimensional but can be three-dimensional, form an essentially distinct category of graphics, but one that is of great importance for information analysis and presentation. Copyright © 2020 Elsevier B.V. or its licensors or contributors. We envision at least three types of infrastructure services that could provide critical support for common problems: data and knowledge management services, integration and translation services, and knowledge discovery services. 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. Populating a virtual environment with seemingly intelligent agents will require substantial advances in all areas of AI, especially the real-time issues of agent architecture (Subsection 3.5). Only recently have researchers begun to apply, to some degree, AI tools and ideas with a view toward automating the hard modeling tasks. by encouraging the use of Intelligent Systems in vehicles The RIC comes in two forms, each adapted to specific control loop and latency requirements: The near real-time RIC (near-RT RIC): Provides programmatic control of open centralized units (O-CUs) and open distributed units (O-DUs) on time cycles of 10ms to 1 second. Machine-learning algorithms identify general trends from specific training data, offering the promise of programs that examine gigabytes of network-accessible data to extract trends that would otherwise go unnoticed by people. People rely on their audience to understand much that is not explicitly said or written, deriving this information from context and common knowledge. However, many high-value applications only require subsets of these capabilities; for example, an intelligent project coach might have only weak real-time requirements and no requirement to behave in a humanlike manner. All rights reserved. The ultimate goal of natural language-processing (NLP[5]) research is to create systems able to communicate with people in natural languages. The Role of the RAN Intelligent Controller in Open RAN Systems The RIC comes in two forms, each adapted to specific control loop and latency requirements: The near real-time RIC (near-RT RIC) : Provides programmatic control of open centralized units (O-CUs) and open distributed units (O-DUs) on time cycles of 10ms to 1 second. Furthermore, consistency is unattainable in a large multisourced system that is being updated continually. And leave to planning algorithms the determination of how to achieve high-level goals can synthesize speech... 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