Behavior in the Ultimatum Game has been well-studied experimentally, and provides a marked contrast between the theoretical model of a self-interested economic agent and that of an actual human concerned with social norms such as fairness. How did such norms evolve, when punishing unfair behavior can be costly to the punishing agent? The work described here simulated a series of Ultimatum Games, in which populations of agents earned resources based on their preferences for proposing and accepting (or rejecting) offers of various sizes. Two different systems governing the acceptance or rejection of offers were implemented. Under one system, the probability that an agent accepted an offer of a given size was independent of the probabilities of accepting the other possible offers. Under the other system, a simple, ordinal constraint was placed on the acceptance probabilities such that a given offer was at least as likely to be accepted as a smaller offer. For simulations under either system, agents’ preferences and their corresponding behavior evolved over multiple generations. Populations without the ordinal constraint came to emulate maximizing economic agents, while populations with the constraint came to resemble the behavior of human players.
UG Sim - Non-monotonic without selection (N = 50)
Ultimatum Game simulation data
UG Sim - Non-monotonic without selection (N
UG Sim - Non-monotonic without selection (N = 100)
Ultimatum Game simulation data
UG Sim - Non-monotonic without selection (N
UG Sim - Non-monotonic without selection (N = 200)
Ultimatum Game simulation data
UG Sim - Non-monotonic without selection (N
UG Sim - Non-monotonic without selection (N = 400)
Ultimatum Game simulation data
UG Sim - Non-monotonic without selection (N
UG Sim - Non-monotonic with selection (N = 50)
Ultimatum Game simulation data
UG Sim - Non-monotonic with selection (N
UG Sim - Non-monotonic with selection (N = 100)
Ultimatum Game simulation data
UG Sim - Non-monotonic with selection (N
UG Sim - Non-monotonic with selection (N = 200)
Ultimatum Game simulation data
UG Sim - Non-monotonic with selection (N
UG Sim - Non-monotonic with selection (N = 400)
Ultimatum Game simulation data
UG Sim - Non-monotonic with selection (N
UG Sim - Monotonic without selection (N = 50)
Ultimatum Game simulation data
UG Sim - Monotonic without selection (N
UG Sim - Monotonic without selection (N = 100)
Ultimatum Game simulation data
UG Sim - Monotonic without selection (N
UG Sim - Monotonic without selection (N = 200)
Ultimatum Game simulation data
UG Sim - Monotonic without selection (N
UG Sim - Monotonic without selection (N = 400)
Ultimatum Game simulation data
UG Sim - Monotonic without selection (N
UG Sim - Monotonic with selection (N = 50)
Ultimatum Game simulation data
UG Sim - Monotonic with selection (N
UG Sim - Monotonic with selection (N = 100)
Ultimatum Game simulation data
UG Sim - Monotonic with selection (N
UG Sim - Monotonic with selection (N = 200)
Ultimatum Game simulation data
UG Sim - Monotonic with selection (N
UG Sim - Monotonic with selection (N = 400)
Ultimatum Game simulation data
UG Sim - Monotonic with selection (N
UG Sim - Non-monotonic, initialized with monotonic procedure (N = 100)
Ultimatum Game simulation data
UG Sim - Non-monotonic, initialized with monotonic procedure (N
UG Sim - Responders initialized to reject all offers (N = 100)
Ultimatum Game simulation data
UG Sim - Responders initialized to reject all offers (N
UG Sim - Responders initialized to accept all offers (N = 100)
Ultimatum Game simulation data
UG Sim - Responders initialized to accept all offers (N
UG Sim - Responders initialized to rational acceptance function (N = 100)
Ultimatum Game simulation data
UG Sim - Responders initialized to rational acceptance function (N
UG Sim - Both roles initialized to rational behavior (N = 100)
Ultimatum Game simulation data
UG Sim - Both roles initialized to rational behavior (N
UG Sim - Proposers constrained to minimum non-zero offer (N = 100)
Ultimatum Game simulation data
UG Sim - Proposers constrained to minimum non-zero offer (N
UG Sim - Responders constrained to accept only hyperfair offers (N = 100)
Ultimatum Game simulation data
UG Sim - Responders constrained to accept only hyperfair offers (N
UG Sim - Roles separate and heritable (N = 100)
Ultimatum Game simulation data
UG Sim - Roles separate and heritable (N
UG Sim - Monotonic with selection, very low mutation rate (N = 100)
Ultimatum Game simulation data
UG Sim - Monotonic with selection, very low mutation rate (N
UG Sim - Monotonic with selection, low mutation rate (N = 100)
Ultimatum Game simulation data
UG Sim - Monotonic with selection, low mutation rate (N
UG Sim - Monotonic with selection, high mutation rate (N = 100)
Ultimatum Game simulation data
UG Sim - Monotonic with selection, high mutation rate (N
UGS Data Legend
PDF file containing details regarding file format and organization