Design of Multiprocessing Systems for Learning Strategies
{'Code': '05010300', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}
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The goal of this research is to develop a multiprocessing system that           automatically learns strategies for dynamic decision problems, both in          hardware and software, such that the strategy learned is targeted for a         multiprocessing system, and that the strategy is the best among those           that can be found in the given time and resource constraints of the             learning system and the knowledge provided by the users.                                                                                                        The class of problems being explored is called dynamic decision                 problems.  These problems may possess one or more of the following              properties:  the decisions necessary to solve the problem may be                interrelated, the decisions are based on dynamic parameters which may           be uncertain, the number of possible strategies is very large, and the          effects of a decision may not be immediately available after the                decision is made.                                                                                                                                               A dynamic decision problem is solved by a combination of domain                 knowledge and meta-knowledge.  Domain knowledge consists of the                 definition of the problem and its parameters, its representation, and           possibly an algorithm (or class of algorithms) to solve it.  Meta-level         knowledge is knowledge about selecting alternatives to implement in the         algorithm and its representation, or finding new ways of solving the            given problem.  Domain knowledge can be implemented in the form of a            program in a computer, for instance, while meta-knowledge is provided           by the designers.                                                                                                                                               This research focuses on the development of methods so that some of the         meta-knowledge supplied by the designers can be obtained by automatic           learning methods.  Initially, the focus is on dynamic decision problems         for which there are some known solutions, and on learning strategies to         solve these problems.  The dynamic decision problems addressed include          combinatorial search problems and real-time decision problems.                                                                                                  The distinguishing features of this research are as follows:  First,            architectural constraints are being included so that the learning               system will find the best strategy given a fixed amount of time and             resources, and the computer on which the learning system is                     implemented.  Second, the strategy learned by the learning system also          includes consideration of the computer on which it will be implemented.         The objectives of this research are to develop methods for automatic            learning and to study multiprocessor architectures suitable for                 learning systems.  This area of research is very important and timely.          The investigator is well qualified to direct this research.  Support is         highly recommended.
{'FirstName': 'Benjamin', 'LastName': 'Wah', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Benjamin W Wah', 'EmailAddress': 'wah@illinois.edu', 'PI_PHON': '2173333516', 'NSF_ID': '000448137', 'StartDate': '12/01/1988', 'EndDate': None, 'RoleCode': 'Principal Investigator'}
{'Name': 'University of Illinois at Urbana-Champaign', 'CityName': 'URBANA', 'ZipCode': '618013620', 'PhoneNumber': '2173332187', 'StreetAddress': '506 S WRIGHT ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'IL13', 'ORG_UEI_NUM': 'Y8CWNJRCNN91', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ILLINOIS', 'ORG_PRNT_UEI_NUM': None}
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[{'Code': '4715', 'Text': 'COMPUTER SYSTEMS ARCHITECTURE'}, {'Code': '6840', 'Text': 'ROBOTICS'}, {'Code': '6856', 'Text': 'ARTIFICIAL INTELL & COGNIT SCI'}]
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