This paper discusses a new architecture for accelerator tuning that combines heuristic and knowle... more This paper discusses a new architecture for accelerator tuning that combines heuristic and knowledge based methods with traditional approaches to control. Control of particle accelerators requires a hybrid architecture, which includes methodologies for planning, intelligent search, and pattern recognition. Control is distributed and hierarchical to utilize parallel problem-solving in the face of time-sensitive control requirements and to decompose complex control problems into more manageable subtasks. For perspective, we discuss past attempts at accelerator control and why these attempts left many issues unresolved.
In this paper, we discuss results of combining various methodologies from the field of artificial... more In this paper, we discuss results of combining various methodologies from the field of artificial intelligence into the design of a control system for accelerator tuning. Our architecture brings together state space search and rule-based reasoning with adaptive/learning algorithms such as fuzzy logic, neural networks and genetic algorithms. We discuss current efforts extending the system to include a general purpose hierarchical control paradigm, parallel distributed reasoning, an object-oriented reasoning structure and additional heuristic control methods.
An important research enterprise for the Artificial Intelligence community since the 1970s has be... more An important research enterprise for the Artificial Intelligence community since the 1970s has been the design of expert or "knowledge-based" systems. These programs used explicitly encoded human knowledge, often in the form of a production rule system, to solve problems in the areas of diagnostics and prognostics. The earliest research/development program in expert systems was created by Professor Edward Feigenbaum at Stanford University . Because the expert system often addresses problems that are imprecise and not fully proposed, with data sets that are often inexact and unclear, the role of various forms of probabilistic support for reasoning is important.
The success of any analogical reasoner depends upon its ability to select a relevant source. We c... more The success of any analogical reasoner depends upon its ability to select a relevant source. We can improve source selection by more completely integrating the process of source retrieval with analogical inference, and by using experience in solving target problems to find properties that effectively predict a source's relevance to future targets. This paper describes the design and evaluation of SCAVENGER, an analogical reasoning program that we have built to test these ideas.
Computer Applications in Medical Care. Computer Systems in Hospitals. Hospital-Based Specialty Care Systems: Automated Information Handling in the Newborn Intensive Care Unit of the University of New Mexico Hospital
... of portable audio (and later video) recording equip-ment, programmed simulated patients andco... more ... of portable audio (and later video) recording equip-ment, programmed simulated patients andcomputers with appropriate ... 4. Scott NC, et al: Interactionanalysis as a meth-od for assessing skill in relating to ... 8. Flanders NA: Teacher Influence, Pupil Attitudes, and Achievement. ...
There are two sections to this paper. The first section briefly lays out the information handling... more There are two sections to this paper. The first section briefly lays out the information handling needs of the Newborn Intensive Care Unit (NICU) of the University of New Mlexico Hospital. The new computer system that we feel best ineets our needs is also introduced. In the second section, the computer hardware is described and then, in some detail, our new software explained. Examples are given of the menu system, the Query by Example routines and the reports the software can generate. 159 0195-4210/83/0000/0159$01.00 i 1983 IEEE
Solving mechanics problems using meta-level inference
Page 1. SOLVING MECHANICS PROBLEMS USING META-LEVEL INFERENCE Alan Bundy, Lawrence Byrd, George L... more Page 1. SOLVING MECHANICS PROBLEMS USING META-LEVEL INFERENCE Alan Bundy, Lawrence Byrd, George Luger, Chris Mellish & Martha Palmer. Department of A rtificial I ntelligence , University of Edinburgh, Edinburgh, Scotland. ...
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