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Friday, May 22, 2020 | History

2 edition of Towards a knowledge-based discrete simulation modelling environment using Prolog found in the catalog.

Towards a knowledge-based discrete simulation modelling environment using Prolog

Ali Ahmad

Towards a knowledge-based discrete simulation modelling environment using Prolog

by Ali Ahmad

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  • 3 Currently reading

Published by typescript in [s.l.] .
Written in English


Edition Notes

Thesis (Ph.D.) - University of Warwick, 1989.

Statementby Ali Ahmad.
ID Numbers
Open LibraryOL13938751M

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Winch Simulation: Multiple, Linked Representations of Linear Functions p. A Learning Environment Based on Multiple Qualitative Models p. EXPITS: An Experimental Environment on ITS p. Intelligent Tutoring System for Symbolic Calculation p. Curriculum Tree: A Knowledge-Based Architecture for Intelligent Tutoring Systems p. This research focuses on the adaptive navigation of maritime autonomous surface ships (MASSs) in an uncertain environment. To achieve intelligent obstacle avoidance of MASSs in a port, an autonomous navigation decision-making model based on hierarchical deep reinforcement learning is proposed. The model is mainly composed of two layers: the scene division layer and an autonomous navigation Cited by: 2.

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Towards a knowledge-based discrete simulation modelling environment using Prolog by Ali Ahmad Download PDF EPUB FB2

Knowledge-Based Systems for Data Modelling: In OSBSS environment, a simulation optimizer interactively communicates with a simulation model to improve the current scheduling with respect to.

Early endeavours of knowledge-based simulation started with building Prolog-based simulation languages such as TS-Prolog (Futó, and Gergely, ), and T-CP (Cleary, Goh, and Unger, ). Holloway L, Krogh B and Giua A () A Survey of Petri Net Methods for Controlled Discrete EventSystems, Discrete Event Dynamic Systems,(), Online publication date: 1-Apr Sloan R and Buy U () Stubborn Sets for Real-Time Petri Nets, Formal Methods in System Design,(), Online publication date: 1-Jul III.

KNOWLEDGE-BASED SIMULATION A. Main Architectures of Knowledge-Based Simulation The history of KBHS started with the connection of simulation and knowl­ edge-based techniques in the early s, first in the ROSS system [20]. As a next step the special simulation languages were developed, for example, T-PROLOG [7] and simulation LISP [9].Cited by: 7.

Knowledge Based Systems. In general they provide a way of applying a set of techniques as well as the technique itself: they are explained further below. In addition, there are specific techniques which may be used in conjunction with any software methodology; the main ones are modelling, simulation and prototyping, and are explained in Section Author: R S Hurst, Carolyn Story.

5 Knowledge based expert systems in testing and design for testability - an overview + Show details-Hide details p. 94 – (28) The application of knowledge based systems to the design of VLSI circuits will have the greatest impact in assisting the engineer with aspects of the design which are not amenable to automation using algorithmic techniques.

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For. Systems Analysis, Modelling and Simulation (Journal of Mathematical Modelling and Simulation in Systems Analysis). Akademieverlag Berlin, Vol. 2,pp. – Google ScholarCited by: 2. Towards an epistemology for Guided Discovery Tutoring: The Popperian connection. A knowledge-based architecture for intelligent tutoring systems.

Pages Chan, Tak -Wai. Book Title Intelligent Tutoring Systems Book Subtitle Second International Conference, ITS '92, Montreal, Canada, June MASON (Luke et al.

) is a fast, easily extendable, discrete event multi-agent simulation toolkit in Java acting as a simulation agent platform. It was designed to serve as the basis for a wide range of multi-agent simulation tasks ranging from swarm robotics to.

ARTIFICIAL INTELLIGENCE (AI) Ma by Dr but a combination of abilities using several cognitive processes to adapt to the environment. Artificial Intelligence is the field dedicated to developing machines that will be able to mimic and perform as humans.

AI or artificial intelligence is the simulation of human intelligence. Thought-capable artificial beings appeared as storytelling devices in antiquity, and have been common in fiction, as in Mary Shelley's Frankenstein or Karel Čapek's R.U.R. (Rossum's Universal Robots).

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A Survey of Knowledge Based Systems in Prolog, Logic Programming Newsletter, Universidade Nova de Lisboa, A Knowledge-Based Expert System for Automatic Analysis and Synthesis in CAD, Proceedings I– AFIPS Press.

A Software Environment for Developing Knowledge-Based Systems, in Computer Science and Technologies Author: Isaac Balbin, Koenraad Lecot. Application Engineering Research Group Alpen-Adria-Universität Klagenfurt Universitätsstraße Klagenfurt am Wörthersee Austria.

Comments from readers of -nets: "Written in a tutorial style, and includes 2 diskettes of NN simulation programs that can be compiled on MS-DOS or Unix (and they do too!)"; "The programs are pretty reasonable as an introduction to some of the things that NNs can do."; "There are *two* editions of this book.

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Heterogeneous hierarchical modeling for knowledge-based autonomous systems Item menu.Discrete event simulation languages. Simulation of inventory and queuing systems: single and multiserver queues, network of queues. Modeling and performance evaluation of computers and computer communication networks.

Workload characterization. Continuous system simulation languages, growth and decay models, system dynamics diagrams.To see a report abstract, click on its number.

Most recently published reports are available for download. If you have queries concerning these or any other publications of the School of Informatics, please contact the School Office. () Ivon Arroyo, Benedict du Boulay, Ulises Xolocotzin Eligio.