AI-based Rock-Paper-Scissors plug and play system

Aphiratsakun, Narong; Blake, Xavier Jonathon; Tin, Kyi Kyi; Ngwe, Tin

doi:10.1109/istem-ed50324.2020.9332629

Cited by 2 publications

(3 citation statements)

References 9 publications

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“…If the output is correct, the results will be compared and player movement will be predicted using the Markov chain. The results of the comparison are displayed in the GUI and the states of the Markov chain are updated [2]. In a Rock, Paper and Scissors game is a well known fact that playing random is the best strategy, best known as Nash Equilibrium.…”

Section: Related Workmentioning

confidence: 99%

Rock, Paper and Scissor Using AI- Random Forest Algorithm

Murukesh

2023

IoT, Cloud and Data Science

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Rock, paper, scissors (RPS) is a game of crucial decision-making that can be used to test various learning algorithms due to its simplicity. Random Forest is a Rock Paper Scissors Agent that makes predictions using the Random Forest Classification with a bit of random. The randomness on this agent has been limited only while losing (and partially due to window length), displaying the algorithm's true potential. A simulation of various AI agents is developed to compare and analyze against the Random forest algorithm.

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Section: Related Workmentioning

confidence: 99%

Rock, Paper and Scissor Using AI- Random Forest Algorithm

Murukesh

2023

IoT, Cloud and Data Science

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“…In other words, this is equivalent to performing reverse engineering to infer the procedure used to generate the time series from the observable time series. Based on this idea, we can used the Markov model as a predictive model, which has been used in many studies [26][27][28][29]. In addition, strategy estimation metaheuristics has been also considered effective in many conventional studies [30][31][32][33].…”

Section: Strategy Inference From Rps Time Series Using Genetic Progra...mentioning

confidence: 99%

“…It is feasible to model the time series of human moves as an output time series from a Markov chain, which allows the player to formulate an effective strategy and estimate the opponent's strategy [26][27][28][29]. Similarly, it is natural idea to employ evolutionary algorithms e.g., genetic algorithms (GA)and genetic programming (GP), to estimate and formulate strategies [30][31][32][33].…”

Section: Introductionmentioning

confidence: 99%

Human Randomness in the Rock-Paper-Scissors Game

2022

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In this study, we investigated the human capacity to generate randomness in decision-making processes using the rock-paper-scissors (RPS) game. The randomness of the time series was evaluated using the time-series data of RPS moves made by 500 subjects who played 50 consecutive RPS games. The indices used for evaluation were the Lempel–Ziv complexity and a determinism index obtained from a recurrence plot, and these indicators represent the complexity and determinism of the time series, respectively. The acquired human RPS time-series data were compared to a pseudorandom RPS sequence generated by the Mersenne Twister and the RPS time series generated by the RPS game’s strategy learned using the human RPS time series acquired via genetic programming. The results exhibited clear differences in randomness among the pseudorandom number series, the human-generated series, and the AI-generated series.

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AI-based Rock-Paper-Scissors plug and play system

Cited by 2 publications

References 9 publications

Rock, Paper and Scissor Using AI- Random Forest Algorithm

Rock, Paper and Scissor Using AI- Random Forest Algorithm

Human Randomness in the Rock-Paper-Scissors Game

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