![]() UNKNOWN - This strategy is included to help you try your own strategies. UNFORGIVING - Cooperate until an opponent defects once, then always defect in each interaction with them. If an opponent defects on this interaction, defect on the next interaction with them. TIT-FOR-TAT - If an opponent cooperates on this interaction cooperate on the next interaction with them. Strategy descriptions are found below: Strategies Each of these determines how many turtles will be created that use the STRATEGY. N-STRATEGY: Multiple sliders exist with the prefix N- then a strategy name (e.g., n-cooperate). GO ONCE: Same as GO except the turtles only take one step. GO: Have the turtles walk around the world and interact. The number of turtles and their strategies are determined by the slider values. ![]() SETUP: Setup the world to begin playing the multi-person iterated prisoner's dilemma. In this model, something good is awarded- money.) HOW TO USE IT Buttons In PD BASIC, you were awarded something bad- jail time. (Note: This way of determining payoff is the opposite of how it was done in the PD BASIC model. When two turtles interact, they display their respective payoffs as labels.Įach turtle's payoff for each round will determined as follows: | Partner's Action While some strategies don't make use of this information, other strategies do.) (Note that each turtle remembers their last interaction with each other turtle. The turtles with different strategies wander around randomly until they find another turtle to play with. One such approach to doing this is to create a world with multiple agents playing a variety of strategies in repeated prisoner's dilemma situations. This makes it difficult to determine a single "best" strategy. Tit-for-tat does poorly with the random strategy, but well with itself. For instance, always defect does best of any against the random strategy, but poorly against itself. Each possible strategy has unique strengths and weaknesses that appear through the course of the game. The PD TWO PERSON ITERATED model demonstrates an interesting concept: When interacting with someone over time in a prisoner's dilemma scenario, it is possible to tune your strategy to do well with theirs. If you are unfamiliar with the basic concepts of the prisoner's dilemma or the iterated prisoner's dilemma, please refer to the PD BASIC and PD TWO PERSON ITERATED models found in the PRISONER'S DILEMMA suite. It is intended to explore the strategic implications that emerge when the world consists entirely of prisoner's dilemma like interactions. This model is a multiplayer version of the iterated prisoner's dilemma. Remember to change the plants/plant breed to the name of your breed.Do you have questions or comments about this model? absorb-CO2 or release-CO2 & be sure to call procedure inside go procedure) add procedure to either absorb or release CO2 (eg.add buttons to call add and remove breed procedures.create a procedure to remove breed to model (eg.create a procedure to add breed to model (eg.create a new turtle shape & setup-default-shape (under setup).Here are the commands, procedures & buttons you will need to setup/update: random 50, generates random numbers from 0 to 50)Ĭreate a new breed that will affect the model (eg. ![]() Run model to 100,000 ticks and record observation. Predict how the new value will affect the model. Change value of the variable in the code. Before changing a variable, setup the model how you will run it each time, then run it to 100,000 ticks and record observation. You will select 3 variables to change in the code.
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