Game: risky food source is 3 if N, 1 if C; safe source is 2
- N: non-contaminated
- C: contaminated
Every agent gets a parameter r between 0 and 1. [or DISCRETE: 8 buckets etc.]
EACH ROUND:
- Nature selects a probability
pfor N - For each agent: if
r>p, then they choose RISKY; else SAFE - Nature flips a coin with bias
pfor N, and announces N or C - If N: everyone who chose RISKY gets 3, everyone who chose SAFE gets 2
- If C: everyone who chose RISKY gets 1, everyone SAFE 2
- Reproduce in proportion to payoff
- Either agent gets # of offspring = payoff [they replace–original “dies off”]
- OR: take the total payoff for RISKYs over total for everyone, there are that proportion of RISKYs in the new population
END ROUND
SEE: We’ll see what are the risk attitudes that are replicated more and less over time
- Install python dependencies as described in the main project readme (requires mesa)
- To run from the main
simulating-riskproject directory:- Configure python to include the current directory in import path;
for C-based shells, run
setenv PYTHONPATH .; for bash, runexport $PYTHONPATH=. - To run interactively with mesa runserver:
mesa runserver simulatingrisk/risky_food/
- Configure python to include the current directory in import path;
for C-based shells, run