rps {sdamr}

Data from Experiment 1 in Guennouni, I., Speekenbrink, M. (2022). Transfer of learned opponent models in repeated games. Computational Brain and Behaviour, 5, 326–342 doi:10.1007/s42113-022-00133-6. Participants (n=52) each play 50 rounds of Rock-Paper-Scissors against an AI player who either adopts a "level-1" or "level-2" strategy. A level-1 strategy assumes the opponent will repeat their last action, and chooses the action that beats this. A level-2 strategy assumes the opponent adopts a level-1 strategy, and chooses the action that beats this. On 10% of rounds, the AI players pick a random action. On the remainder, they act according to their strategy.

Description

\@format A data frame with 2600 observations of 6 variables:

id

(factor) Participant ID

ai_strategy

(factor) Strategy adopted by AI player

round

(numeric) Round number (between 1 and 50)

human_action

(factor) Action taken by human (rock, paper, or scissors)

ai_action

(factor) Action taken by AI (rock, paper, or scissors)

score

(numeric) Outcome for human player, where 1 indicates a win, -1 a loss, and 0 a tie

Usage

rps

Format

An object of class data.frame with 2600 rows and 6 columns.

Source

Guennouni, I., Speekenbrink, M. (2022). Transfer of learned opponent models in repeated games. Computational Brain and Behaviour, 5, 326–342. doi:10.1007/s42113-022-00133-6