initialize the transition, observation, and reward matrices given a transition function, reward function, and state space
fisheries_matrices(states = 0:20, actions = states, observed_states = states, reward_fn = function(x, a) pmin(x, a), f = ricker(1, 15), sigma_g = 0.1, sigma_m = 0.1, noise = c("rescaled-lognormal", "lognormal", "uniform", "normal"))
| states | sequence of possible states |
|---|---|
| actions | sequence of possible actions |
| observed_states | sequence of possible observations |
| reward_fn | function of x and a that gives reward for tacking action a when state is x |
| f | transition function of state x and action a. |
| sigma_g | half-width of uniform shock or equivalent variance for log-normal |
| sigma_m | half-width of uniform shock or equivalent variance for log-normal |
| noise | distribution for noise, "lognormal" or "uniform" |
list of transitition matrix, observation matrix, and reward matrix
assumes log-normally distributed observation errors and process errors