gento find either full or partial policy, or just a best action fot given state.
gen, but your model defines only
transition, then there is a default
genimplementation that calls
rand(transition(…))But someone else should confirm.
transitionfunction defined for your wrapper (it can't be both). Since the underlying MMDP is defined by a
genfunction I think you need to define an appropriate
genfunction for your wrapper mmdp.
[slack] <pure_interpeter> Usage:
mdp = LastActionWrapper(FirstOrderMultiUAVDelivery())
solver = FVMCTSSolver(;coordination_strategy=MaxPlusWithCost(agent_action_cost=zeros(11), joint_action_cost=zeros(11,11)))
planner = solve(solver, mdp)
s = rand(initialstate(mdp))
a = action(planner, s)`
[slack] <sunbergzach> Hey @Jan Mrkos, @pure_interpeter, and @rejuvyesh, sorry for not monitoring this channel; I was quite busy with the start of the semester. Regarding the original question,
What is the motivation behind gen and what does it do?
that is somewhat confusing, so I have added an FAQ: https://juliapomdp.github.io/POMDPs.jl/latest/faq/#What-is-the-difference-between-transition,-gen,-and-@gen? and also updated the main docs about defining problems