Analisis Perbandingan Kecerdasan Buatan pada Computer Player dalam Mengambil Keputusan pada Game Battle RPG

Abdi, Musta'inul; Herumurti, Darlis; Kuswardayan, Imam

doi:10.12962/j24068535.v15i2.a671

Cited by 4 publications

(4 citation statements)

References 10 publications

(15 reference statements)

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“…Artificial intelligence is a technology that can make decisions by analyzing and using the data available in the system [7].…”

Section: Introductionmentioning

confidence: 99%

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Backtracking and k-Nearest Neighbour for Non-Player Character to Balance Opponent in a Turn-Based Role Playing Game of Anagram

Prakosa

Suni

2022

khif

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Anagram is a turn-based role-playing game where two players construct words by arranging given letters. A significant aspect of playing a game is the challenge. A good challenge comes from an opponent with a close ability. In a two-player game like Anagram, the second player can be a nonhuman player called Non-Playable Character (NPC). A balanced game is more engaging. Therefore, it is imperative to insert artificial intelligence (AI) into an NPC to make it possess a balance ability. This study investigates the AI algorithm that is the most appropriate to make a balance NPC for Anagram games. We tested three scenarios: Descending AI, Random AI, and AI with k-Nearest Neighbour (k-NN). Descending AI gets an Anagram solution by selecting a word with the highest score from all possible answers. Random AI picks a word randomly from the possible answers, while AI with k-NN chooses a word closest to one of the human players. The results show that Descending AI is the best algorithm to make the strongest NPC, which always gets the highest score, followed by Random AI and AI with k-NN. However, AI with the k-NN algorithm makes the constructed NPC has the highest number of turns at an average of 18, while Descending AI gets 14 turns and Random AI has 15 turns. Looking at the remaining lives at the end of the game, AI with k-NN makes the NPC has 25 lives left, while Descending AI has 59 lives, and Random AI has 48 lives. Less remaining lives suggest that NPC containing AI with the k-NN algorithm matches closer to the human player and therefore is more suitable for Anagram NPC.

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“…Artificial intelligence is a technology that can make decisions by analyzing and using the data available in the system [7].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, intelligent AI is needed for NPCs to be able to keep up with players [9]. Several methods can be used to provide intelligence to NPCs, for example, fuzzy [5] and rule base [7]. The rule base method applies the rules according to the situation and actions [10].…”

Section: Introductionmentioning

confidence: 99%

Backtracking and k-Nearest Neighbour for Non-Player Character to Balance Opponent in a Turn-Based Role Playing Game of Anagram

Prakosa

Suni

2022

khif

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“…Today, in Industrial 4.0 era, Artificial Intelligent (AI) is utilized rapidly in many sector and various case study [6], [7], either in economic [8], medicine [9], education [10], [11], game [12], [13], health [14]- [16], and so on. AI technology make computer more intelligent so that can solve various and complex problem.…”

Section: Introductionmentioning

confidence: 99%

Expert System for Predicting Children Mental Retardation using Forward Chaining

Hays¹,

Suhendar²,

Amaliah³

et al. 2020

Selected Papers From the 1st International Conference on Islam, Science and Technology, ICONISTECH-1 2019, 11-12 July 2019, Ban

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“…Dari uraian diatas menunjukkan bahwa penggunaan kecerdasan buatan di dalam game dibutuhkan untuk meningkatkan tantangan di dalam game. Membuat game menjadi lebih dinamis dan dapat menunjang realitas game, sehingga akan menciptakan kesenangan bagi pengguna pada saat memainkan game dan ketertarikan pengguna untuk memainkan game juga akan meningkat (Abdi et al, 2017). Anak usia dini sangat membutuhkan pola atau cara belajar yang menarik dimana dengan memanfaatkan teknologi yang ada saat ini dapat membuat mereka berfikir bahwa belajar adalah suatukegiatan yang menyenangkan karena mereka dapat bermain sekaligus belajar (Jayanti et al, 2018).…”

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Penerapan AI Melalui Pendekatan Heuristik Semilaritas Pada Game Edukasi Anak Usia Dini

Sahputra

Muzakir

2021

JPSII

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Game is one of the rapidly growing industries in everyday life. Currently the game is very popular in all circles, both among children, teenagers and adults. However, there are still many games that only prioritize addictive elements and ignore educational elements. Therefore, here the author will build a game that has an educational element as a learning medium. This study will apply AI to an early childhood educational game through a heuristic semilarity approach to the habits of early childhood in answering questions such as equating in everyday life. This research will produce a game that can improve intelligence, creativity and memory at an early age such as guessing pictures, counting and arranging words randomly.

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Analisis Perbandingan Kecerdasan Buatan pada Computer Player dalam Mengambil Keputusan pada Game Battle RPG

Cited by 4 publications

References 10 publications

Backtracking and k-Nearest Neighbour for Non-Player Character to Balance Opponent in a Turn-Based Role Playing Game of Anagram

Backtracking and k-Nearest Neighbour for Non-Player Character to Balance Opponent in a Turn-Based Role Playing Game of Anagram

Expert System for Predicting Children Mental Retardation using Forward Chaining

Penerapan AI Melalui Pendekatan Heuristik Semilaritas Pada Game Edukasi Anak Usia Dini

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