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Implementasi fuzzy state machine untuk mengatur perilaku NPC (musuh) dalam game Sharaf
Get PDFINDONESIA:
Game Sharaf merupakan game bergenre adventure, dimana terdapat 2 misi yakni mengumpulkan lafadz dan menyusun lafadz. Untuk menyelesaikan misi 1, pemain dihadapkan dengan NPC (musuh) berupa naga yang perilakunya bisa berubah. Non- Player Character (NPC) merupakan karakter pada game yang bergerak otomatis tanpa kendali pemain. Penelitian ini membahas tentang bagaimana membuat NPC berperilaku cerdas yang perilakunya berubah sesuai dengan variable yang dimiliki. Untuk memberikan kecerdasan pada NPC digunakan kecerdasan buatan (Artificial Intelligence) yakni metode Fuzzy State Machine yang merupakan gabungan dari Finite State Machine untuk memodelkan perilaku NPC dan logika Fuzzy untuk menghasilkan keputusan perilaku NPC yang variatif apakah NPC berperilaku bersiap, mendekat atau menembak. Dalam penelitian ini digunakan Fuzzy Sugeno karena keluarannya berupa konstanta tegas yang nilainya mewakili tiap perilaku dengan 3 inputan yakni jarak, skor dan kemampuan. Hasil dari penelitian ini membuktikan bahwa metode Fuzzy State Machine dapat menjadikan NPC berperilaku dinamis dan variatif sesuai dengan variable input yang dimilki.
ENGLISH:
Sharaf game is a adventure type game where have 2 goals : collect words and arrange words. To solve the first goal, the player faced with non-player character (NPC) which have changeable behaviour. Non-Player character (NPC) is a character in game which have automatic movement without controlled by player. This research explain about how to make Non-Player Character (NPC) have intelligent behavior which the behavior can change suitable with variable of his. To give an intelligent, used an artificial intelligence “Fuzzy State Machine”. Fuzzy State Machine is a method combination from Finite State Machine to modelling behavior of Non-Player Character (NPC) and Fuzzy Logic to produce a decision variational behavior of NPC, what the NPC get prepared, or came near or shoot. This research, use Fuzzy Sugeno because the output of it is a crisp value which the value can represent every behavior with 3 inputs : distance, score and ability. The result of this research, give evidence that Fuzzy State Machine can make the NPC have dynamic behavior and variation suitable with variable input he has
Non-Playable Character Adaptif pada Game RPG Menggunakan Metode Logarithmic Learning For Generalized Classifier Neural Network (L-GCNN)
Get PDFNon-playable Character (NPC) merupakan salah satu karakter yang penting dalam game. NPC yang bersifat otonom dan adaptif, dapat menyesuaikan aksi dengan aksi pemain dan keadaan lingkungan. Untuk menentukan aksi NPC, peneliti sebelumnya menggunakan metode Neural Network namun terdapat kelemahan yakni aksi yang dihasilkan tidak sesuai dengan yang diinginkan sehingga akurasinya kurang baik. Penelitian ini mengatasi masalah akurasi yang kurang baik dengan menggunakan metode Logarithmic Learning for Generalized Classifier Neural Network (L-GCNN) dengan menggunakan 6 parameter input yakni kesehatan NPC, jarak dengan pemain, NPC lain terlibat atau tidak, daya serang, jumlah NPC dan level NPC. Sedangkan outputnya yakni menyerang sendiri, menyerang berkelompok dan menjauh.
Untuk pengujian, penelitian ini diuji cobakan pada game RPG. Dari hasil uji coba yang dilakukan menunjukkan bahwa metode L-GCNN memiliki akurasi yang lebih baik dari 3 metode yang dibandingkan yakni 7% lebih baik dari NN dan SVM serta lebih baik 8% dari RBFNN karena pada metode L-GCNN terdapat proses enkapsulasi yakni data yang mempunyai kelas yang sama akan dikelompokkan menjadi satu. Sedangkan untuk waktu training L-GCNN lebih lama 30% dari metode NN karena pada L-GCNN satu neuron terdiri dari satu data dimana pada NN lebih sedikit neuron pada hidden layer.
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Non-playable Character (NPC) is one of the important characters in the game. NPCs that are autonomous and adaptive, can adjust actions with player actions and environmental conditions. To determine the actions of the NPC, the previous researchers used the Neural Network method but there were weaknesses, namely the action produced was not in accordance with the desired so the accuracy was not good. This study overcomes the problem of accuracy that is not good by using the Logarithmic Learning for Generalized Classifier Neural Network (L-GCNN) method using 6 input parameters namely NPC health, distance with players, other NPCs involved or not, attack power, number of NPCs and NPC levels . While the output is single attack, keep the distance and attacking in group.For testing, this study was tested on RPG games. From the results of the experiments conducted shows that the L-GCNN method has better accuracy than the 3 methods compared to 7% better than NN and SVM and 8% better than RBFNN because in the L-GCNN method there is an encapsulation process that is data having the same class will be grouped together. Whereas the L-GCNN training time is 30% longer than the NN method because on L-GCNN one neuron consists of one data where in NN there are fewer neurons in thehidden layer
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Adaptive Non Playable Character in RPG Game Using Logarithmic Learning For Generalized Classifier Neural Network (L-GCNN)
Get PDFNon-playable Character (NPC) is one of the important characters in the game. An autonomous and adaptive NPC can adjust actions with player actions and environmental conditions. To determine the actions of the NPC, the previous researchers used the Neural Network method but there were weaknesses, namely the action produced was not in accordance with the desired so the accuracy was not good. This study overcomes the problem of poor accuracy by using the Logarithmic Learning for Generalized Classifier Neural Network (L-GCNN) method with 6 input parameters, NPC health, distance from players, other NPCs involved, attack power, number of NPCs and NPC levels. While the output is to attack itself, attack in groups and move away. For testing, this study was tested on RPG games. From the results of the experiments conducted, it shows that the L-GCNN method has better accuracy than the 3 methods compared to 7% better than NN and SVM and 8% better than RBFNN because in the L-GCNN method there is an encapsulation process that is data have the same class will. Whereas the L-GCNN training time is 30% longer than the NN method because on L-GCNN one neuron consists of one data where there are fewer NNs in the hidden layer
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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