18 research outputs found

    Shallow Binding in LISP 1.5

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    Key Words and Phrases: LISP 1.5, environment structures, FUNARGs, shallow and deep binding, multiprogramming, cache. CR Categories: 4.13, 4.22, 4.32 This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-75-C-0522.Shallow binding is a scheme which allows the value of a variable to be accessed in a bounded amount of computation. An elegant model for shallow binding in LISP 1.5 is presented in which context-switching is an environment structure transformation called "re-rooting". Re-rooting is completely general and reversible, and is optional in the sense that a LISP 1.5 interpreter will operate correctly whether or not re-rooting is invoked on every context change. Since re-rooting leaves (ASSOC X A) invariant, for all variables X and all environments A, the programmer can have access to a re-rooting primitive, (SHALLOW), which gives him dynamic control over whether accesses are shallow or deep, and which effects only the speed of execution of a program, not its semantics. So long as re-rooting is an indivisible operation, multiple processes can be active in the same environment structure. The re-rooting scheme is compared to a cache scheme for shallow binding and the two are found to be compatible. Finally, the concept of re-rooting is shown not to depend upon LISP's choice of dynamic instead of lexical binding for free variables; hence it can be used in an Algol interpreter, for example.MIT Artificial Intelligence Laboratory Department of Defense Advanced Research Projects Agenc

    Spatial point processes: from the mathematical basis to its applications

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    Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2023, Director: Carles Rovira Escofet i Jorge Mateu[en] This work is a study about the spatial point processes. We study the mathematical basis of this object, we expose statistic tools which are used in the analysis of spatial point patterns and, finally, we apply all the exposed theory in a real case study with real data. In the first and second chapter we present the mathematical theory behind the spatial point processes. In the starting chapter we find the most general and abstract definitions, and the very definition of a spatial point process. In this chapter we have used Stoyan et al. 2013 [17]. In the second chapter, using as a reference Diggle 2013 [10], we explain the mathematical theory of the point processes in tha plane. We define and study the properties of several types of processes, and different quantities which are hugely important in the study of this kind of objects. In the third chapter, based mainly in Baddeley et al. (2015) [2], we present, giving examples, the statistic tools used in the analysis of point processes in the plane. The tools exposed are related with the theory exposed previously and are used in the last chapter of the project. Finally, in the last chapter, we put into practice all the knowledge we have acquired in a real case study. Using the database employed in Jorge Mateu, P. Diggle and I. Tamayo-Uria (2014) [18], shared by Jorge Mateu, we perform a study about the rat and cockroach sightings in Madrid city. This constitutes an application in a real public health case of the concepts seen during the work

    A programmers guide to MMT.

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    Metode Ensembel Rock dan SWFM untuk pengelompokan data campuran Numerik dan kategorik pada kasus aksesi jeruk

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    Salah satu permasalahan yang sering ditemui dalam analisis kelompok adalah data yang berskala campuran numerik dan kategorik. Metode untuk mengelompokkan data campuran diantaranya metode ensembel dan metode Similarity Weight and Filter Method (SWFM). Tahap pengelompokan metode ensembel dilakukan dengan algoritma pengelompokan data kategorik, salah satunya adalah metode ROCK (RObust Clustering using linKs). Terdapat banyak penelitian dan pengembangan mengenai kedua metode tersebut, namun penelitian mengenai perbandingan kinerja dari kedua metode masih terbatas. Oleh karena itu, penelitian ini melakukan perbandingan kinerja antara metode ensembel ROCK dan ensembel SWFM. Kedua metode digunakan pada studi kasus pengelompokkan aksesi jeruk hasil fusi protoplasma yang merupakan data campuran numerik dan kategorik. Metode pengelompokan terbaik ditentukan dengan kriteria rasio antara simpangan baku di dalam kelompok (SW) dan simpangan baku antar kelompok (SB) terkecil. Berdasarkan 25 objek pengamatan pada studi kasus, metode ensembel ROCK dengan nilai θ sebesar 0,27 menghasilkan tiga kelompok dengan nilai rasio sebesar 0,1358, sedangkan metode ensembel SWFM menghasilkan dua kelompok dengan nilai rasio sebesar 0,3059. Hasil tersebut menunjukkan bahwa metode ensembel ROCK memberikan kinerja pengelompokan lebih baik daripada metode ensembel SWFM. Karakteristik hasil ensembel ROCK yang diperoleh adalah (a) kelompok 1 beranggotakan 10 aksesi dengan buah berukuran kecil tetapi berat, berkulit tebal, berwarna dominan kuning kehijauan, permukaan dominan halus, tekstur pulp beragam, dan berkadar air sedang, (b) kelompok 2 beranggotakan 7 aksesi dengan buah berukuran sedang tetapi berat, berkulit tipis, warna kulit beragam, permukaan beragam, tekstur pulp beragam, dan berkadar air tinggi, dan (c) kelompok 3 beranggotakan 3 aksesi dengan buah berukuran besar tetapi ringan, berkulit tebal, berwarna kuning kehijauan, permukaan halus, pulp lembut, dan berkadar air sedang. ============================================================================= One of the problems often encountered in clustering analysis (cluster) is a mixed numerical and categorical dataset. The method is used to analyze the mixed dataset including ensemble method and Similarity Weight and Filter Method (SWFM) method. In the ensemble method, the clustering is done with categorical data clustering algorithm, one of them is a ROCK method (Robust Clustering using links). There is a lot of research and development concerning both methods, but research about performance comparative between methods is still limited. Therefore, this study do a performance comparison between the ensemble ROCK method and ensemble SWFM method. Both of these method are used for the case study about clustering of citrus accessions which have a mixed numerical and categorical dataset. Best clustering method is determined by the smallest rasio of standard deviation in groups (SW) and standard deviation between groups (SB). Clustering result for 25 observation obtained by using the ensemble ROCK method with values of θ is 0,27 produces three groups of data with ratio value of 0,1358, while the ensemble SWFM method produces two groups of data with ratio value of 0,3059. These results suggest that ROCK ensemble method provides better performance than the ensemble SWFM method. Characteristics of ensemble ROCK’s results are (a) group 1 consisted of 10 accessions with a small but heavy fruit, thick-skinned, the color dominant greenish yellow, predominantly smooth surface, diverse pulp, and medium water content, (b) group 2 consisted of 7 accession with medium size but heavy fruit, thin-skinned, variety color, diverse surface, diverse pulp, and high water content, and (c) group 3 consists of 3 accession with large but lightweight fruit, thick-skinned, yellow-green color, smooth surface, soft pulp, and medium water content

    Hierarchy in Knowledge Representations

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    This research was conducted at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the Laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract number N00014-75-C-0643.This paper discusses a number of problems faced in communicating expertise and common sense to a computer, and the approaches taken by several current knowledge representation languages towards solving these problems. The main topic discussed is hierarchy. The importance of hierarchy is almost universally recognized. Hierarchy forms the backbone of many existing representation languages. We discuss several technical problems raised in constructing hierarchical and almost hierarchical systems as criteria and open problems.MIT Artificial Intelligence Laboratory Department of Defense Advanced Research Projects Agenc

    The preservation of the environment.

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    Interactive program verification using virtual programs

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    This thesis is concerned with ways of proving the correctness of computer programs. The first part of the thesis presents a new method for doing this. The method, called continuation induction, is based on the ideas of symbolic execution, the description of a given program by a virtual program, and the demonstration that these two programs are equivalent whenever the given program terminates. The main advantage of continuation induction over other methods is that it enables programs using a wide variety of programming constructs such as recursion, iteration, non-determinism, procedures with side-effects and jumps out of blocks to be handled in a natural and uniform way. In the second part of the thesis a program verifier which uses both this method and Floyd's inductive assertion method is described. The significance of this verifier is that it is designed to be extensible, and to this end the user can declare new functions and predicates to be used in giving a natural description of the program's intention. Rules describing these new functions can then be used when verifying the program. To actually prove the verification conditions, the system employs automatic simplification, a relatively clever matcher, a simple natural deduction system and, most importantly, the user's advice. A large number of commands are provided for the user in guiding the system to a proof of the program's correctness. The system has been used to verify various programs including two sorting programs and a program to invert a permutation 'in place' the proofs of the sorting programs included a proof of the fact that the final array was a permutation of the original one. Finally, some observations and suggestions are made concerning the continued development of such interactive verification systems
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