I have a slot machine simulator (see code below) I would like to run the simulator 5000 and store the result (prize) into a dataset. My idea is to have three variables in the dataset: simnumber; prize; cumulative. Simnumber: is the number of the simulation (1 to 5000). Slot Machine Simulation Using Visual C#A slot machine is a gambling device into which the user inserts money and then pulls a lever (or presses a button). 26 votes, 23 comments. I've been hunting for an emulator that uses US based slot machines. I've seen Fruit-Emu, but everything on looks to be UK.

Abstract

The present article describes a software program in Visual Basic .NET designed to simulate three slot machines on a computer screen. This software is described in detail regarding utility, downloading, and usage; and data are presented illustrating the software’s potential for researchers interested in gambling behavior. A simulation of multiple slot machines such as this enables researchers to evaluate players’ preferences across various machines. In the highlighted experiment, 18 recreational slot machine players played the software for extra course credit and a chance at cash prizes. All participants played a version of the simulation in which every 5th response on average was a win, whereas the remaining trials were a loss. However, on those loss trials, a varying distribution of almost wins or near misses (i.e., two winning symbols on the payoff line and the final winning symbol directly above or below the payoff line) were presented in percentages of 15, 30, or 45. While no preferences across the three options could be predicted on the basis of reinforcement history alone, deviations from equal choices across the games were noted and appeared to be the result of the presentations of near-miss losing trials. Implications for a greater understanding of pathological gambling are presented.

References

  1. Dixon, M. R., &Delaney, J. (2006). The impact of verbal behavior on gambling behavior. In P. M. Ghezzi, C. A. Lyons, M. R. Dixon, & G. R. Wilson (Eds.),Gambling: Behavior theory, research, and application (pp. 171–189). Reno, NV: Context Press.

  2. Dixon, M. R., MacLin, O. H., &Daugherty, D. (2006). Response allocations to concurrently available slot machine simulations.Behavior Research Methods,38, 232–236.

  3. Dixon, M. R., &Moore, K. (2006). Native American gambling: The quest for the new white buffalo. In P. M. Ghezzi, C. A. Lyons, M. R. Dixon, & G. R. Wilson (Eds.),Gambling: Behavior theory, research, and application (pp. 231–247). Reno, NV: Context Press.

  4. Dixon, M. R., &Schreiber, J. E. (2004). Near-miss effects on response latencies and win estimations of slot machine players.Psychological Record,54, 335–348.

  5. Ghezzi, P. M., Lyons, C. A., &Dixon, M. R. (2000). Gambling in socioeconomic perspective. In W. K. Bickel & R. E. Vuchinich (Eds.),Reframing health behavior change with behavioral economics (pp. 313–338). Mahwah, NJ: Erlbaum.

  6. Lesieur, H. R., &Blume, S. B. (1987). The South Oaks Gambling Screen (SOGS): A new instrument for the identification of pathological gamblers.American Journal of Psychiatry,144, 1184–1188.

  7. MacLin, O. H., Dixon, M. R., &Hayes, L. J. (1999). A computerized slot machine simulation to investigate the variables involved in gambling behavior.Behavior Research Methods, Instruments, & Computers,31, 731–735.

  8. MacLin, O. H., Dixon, M. R., Robinson, A., &Daugherty, D. (2006). Writing a simple slot machine simulation program. In P. M. Ghezzi, C. A. Lyons, M. R. Dixon, & G. R. Wilson (Eds.),Gambling: Behavior theory, research, and application (pp. 127–154). Reno, NV: Context Press.

  9. Shaffer, H. J., Hall, M. N., &Vander Bilt, J. (1999). Estimating the prevalence of disordered gambling behavior in the United States and Canada: A research synthesis.American Journal of Public Health,89, 1369–1376.

  10. Stewart, R. M., &Brown, R. I. F. (1988). An outcome study of Gamblers Anonymous.British Journal of Psychiatry,152, 284–288.

Slot machine simulation code

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Correspondence to Mark R. Dixon.

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Slot Machine Simulation C

MacLin, O.H., Dixon, M.R., Daugherty, D. et al. Using a computer simulation of three slot machines to investigate a gambler’s preference among varying densities of near-miss alternatives. Behavior Research Methods39, 237–241 (2007). https://doi.org/10.3758/BF03193153

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.3758/BF03193153

Keywords

  • Pathological Gambling
  • Gambling Behavior
  • Extinction Condition
  • Slot Machine
  • Visual Basic

Abstract

The present article describes a software program in Visual Basic .NET designed to simulate three slot machines on a computer screen. This software is described in detail regarding utility, downloading, and usage; and data are presented illustrating the software’s potential for researchers interested in gambling behavior. A simulation of multiple slot machines such as this enables researchers to evaluate players’ preferences across various machines. In the highlighted experiment, 18 recreational slot machine players played the software for extra course credit and a chance at cash prizes. All participants played a version of the simulation in which every 5th response on average was a win, whereas the remaining trials were a loss. However, on those loss trials, a varying distribution of almost wins or near misses (i.e., two winning symbols on the payoff line and the final winning symbol directly above or below the payoff line) were presented in percentages of 15, 30, or 45. While no preferences across the three options could be predicted on the basis of reinforcement history alone, deviations from equal choices across the games were noted and appeared to be the result of the presentations of near-miss losing trials. Implications for a greater understanding of pathological gambling are presented.

References

  1. Dixon, M. R., &Delaney, J. (2006). The impact of verbal behavior on gambling behavior. In P. M. Ghezzi, C. A. Lyons, M. R. Dixon, & G. R. Wilson (Eds.),Gambling: Behavior theory, research, and application (pp. 171–189). Reno, NV: Context Press.

  2. Dixon, M. R., MacLin, O. H., &Daugherty, D. (2006). Response allocations to concurrently available slot machine simulations.Behavior Research Methods,38, 232–236.

  3. Dixon, M. R., &Moore, K. (2006). Native American gambling: The quest for the new white buffalo. In P. M. Ghezzi, C. A. Lyons, M. R. Dixon, & G. R. Wilson (Eds.),Gambling: Behavior theory, research, and application (pp. 231–247). Reno, NV: Context Press.

  4. Dixon, M. R., &Schreiber, J. E. (2004). Near-miss effects on response latencies and win estimations of slot machine players.Psychological Record,54, 335–348.

  5. Ghezzi, P. M., Lyons, C. A., &Dixon, M. R. (2000). Gambling in socioeconomic perspective. In W. K. Bickel & R. E. Vuchinich (Eds.),Reframing health behavior change with behavioral economics (pp. 313–338). Mahwah, NJ: Erlbaum.

  6. Lesieur, H. R., &Blume, S. B. (1987). The South Oaks Gambling Screen (SOGS): A new instrument for the identification of pathological gamblers.American Journal of Psychiatry,144, 1184–1188.

  7. MacLin, O. H., Dixon, M. R., &Hayes, L. J. (1999). A computerized slot machine simulation to investigate the variables involved in gambling behavior.Behavior Research Methods, Instruments, & Computers,31, 731–735.

  8. MacLin, O. H., Dixon, M. R., Robinson, A., &Daugherty, D. (2006). Writing a simple slot machine simulation program. In P. M. Ghezzi, C. A. Lyons, M. R. Dixon, & G. R. Wilson (Eds.),Gambling: Behavior theory, research, and application (pp. 127–154). Reno, NV: Context Press.

  9. Shaffer, H. J., Hall, M. N., &Vander Bilt, J. (1999). Estimating the prevalence of disordered gambling behavior in the United States and Canada: A research synthesis.American Journal of Public Health,89, 1369–1376.

  10. Stewart, R. M., &Brown, R. I. F. (1988). An outcome study of Gamblers Anonymous.British Journal of Psychiatry,152, 284–288.

Author information

Affiliations

Slot Machine Simulation C#

Corresponding author

Correspondence to Mark R. Dixon.

Rights and permissions

About this article

Cite this article

MacLin, O.H., Dixon, M.R., Daugherty, D. et al. Using a computer simulation of three slot machines to investigate a gambler’s preference among varying densities of near-miss alternatives. Behavior Research Methods39, 237–241 (2007). https://doi.org/10.3758/BF03193153

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.3758/BF03193153

Slot Machine Simulator Game

Keywords

Slot Machine Simulation C#

  • Pathological Gambling
  • Gambling Behavior
  • Extinction Condition
  • Slot Machine
  • Visual Basic

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