model from log

model from log

models_from_log(meta, reward_fn = function(x, h) pmin(x, h))

Arguments

meta	a data frame containing the log metadata for each set of alpha vectors desired, see meta_from_log
reward_fn	a function f(x,a) giving the reward for taking action a given a system in state x.

Value

a list with an element for each row in the requested meta data frame, which itself is a list of the three matrices: transition, observation, and reward, defining the pomdp problem.

Details

assumes transition can be determined by the f_from_log function, which is specific to the fisheries example

Examples

# NOT RUN {
source(system.file("examples/fisheries-ex.R", package = "sarsop"))
log = tempfile()
alpha <- sarsop(transition, observation, reward, discount, precision = 10,
                log_dir = log, log_data = log_data)

## Get metadata for all logged solutions matching the desired query
meta <- meta_from_log(parameters = data.frame(model = "ricker", r = 0.1), log_dir = log)
alphas <- alphas_from_log(meta, log_dir = log)
fs <- f_from_log(meta)
models <- models_from_log(meta)
# }