Utility Function Decision-Making Simulation
Budget: $15 – $25 USD
I seek a capable freelancer to develop a simulation platform that focuses on individuals choosing between one of three utility functions within a population.
The three utility functions are
Self interest: Utility = Immediate Payoff
Empathy: Utility = QG(IP) + (EF * QG (OP))
Where QG is a qualitative growth factor,
EF is the empathy factor, and OP is the payoff of the other player
Dark Empathy: QG (IP) + (EF * QG (IP - OP))
(One player benefits from the other players loss)
I would like to structure the simulation where individuals are randomly paired up and engage in a series of games for each period of time. Games will have a variable range of payouts. For example, the prisoner's dilemma, the public goods game, etc.
The ultimate goal of the simulation is to:
- Analyze decision-making behavior within a population
- Enable insights into population dynamics
- Show which strategy dominates given certain conditions
To reinforce the complexity and reality of the simulation, the decision-making process of individuals should consider the following influences:
- Inherent utility
- Behavioral elasticity
- The degree of trust within interactions (self-interest and dark empathetic strategies decrease trust, empathetic strategies increase trust)
The utility function must be calculated using a combination of various factors, which will need careful integration into the algorithm.
I would like to work with you to develop further assumptions, for example, an individual's resources increase as their utility increases, empathy increases when certain resource thresholds are met, empathy increases as it is used, etc.
Ideal skills and experience for the project:
- Proven expertise in developing simulations
- Solid understanding of utility theory
- Experience in modeling behavioral influences in decision-making
- Exceptional in algorithm development and system integration
- Familiarity with game theory
The aim is to make the simulation as realistic and applicable as possible. I look forward to seeing how you could shape these concepts into a functional tool.
The three utility functions are
Self interest: Utility = Immediate Payoff
Empathy: Utility = QG(IP) + (EF * QG (OP))
Where QG is a qualitative growth factor,
EF is the empathy factor, and OP is the payoff of the other player
Dark Empathy: QG (IP) + (EF * QG (IP - OP))
(One player benefits from the other players loss)
I would like to structure the simulation where individuals are randomly paired up and engage in a series of games for each period of time. Games will have a variable range of payouts. For example, the prisoner's dilemma, the public goods game, etc.
The ultimate goal of the simulation is to:
- Analyze decision-making behavior within a population
- Enable insights into population dynamics
- Show which strategy dominates given certain conditions
To reinforce the complexity and reality of the simulation, the decision-making process of individuals should consider the following influences:
- Inherent utility
- Behavioral elasticity
- The degree of trust within interactions (self-interest and dark empathetic strategies decrease trust, empathetic strategies increase trust)
The utility function must be calculated using a combination of various factors, which will need careful integration into the algorithm.
I would like to work with you to develop further assumptions, for example, an individual's resources increase as their utility increases, empathy increases when certain resource thresholds are met, empathy increases as it is used, etc.
Ideal skills and experience for the project:
- Proven expertise in developing simulations
- Solid understanding of utility theory
- Experience in modeling behavioral influences in decision-making
- Exceptional in algorithm development and system integration
- Familiarity with game theory
The aim is to make the simulation as realistic and applicable as possible. I look forward to seeing how you could shape these concepts into a functional tool.