update

src/mcts.jl

@@ -52,7 +52,7 @@ using GeneralUtils
   Signature\n
   -----
 """
-struct MCTSNode{T}
+struct MCTSNode{T<:AbstractDict}
   state::T
   visits::Integer
   stateValue::AbstractFloat
@@ -129,7 +129,7 @@ end
   -----
 """
 function expand(node::MCTSNode, state::T, decisionMaker::Function, stateValueEstimator::Function;
-                n::Integer=3) where {T<:Any}
+                n::Integer=3) where {T<:AbstractDict}
 
   # sampling action from decisionMaker
   for sample in 1:n
@@ -164,7 +164,7 @@ end
   Signature\n
   -----
 """
-function simulate(state::T, max_depth::Int) where {T<:Any}
+function simulate(state::T, max_depth::Int) where {T<:AbstractDict}
     total_reward = 0.0
     for _ in 1:max_depth
       #[] Implement your action selection function based on highest stateValue
@@ -264,7 +264,7 @@ end
 """
 isLeaf(node::MCTSNode)::Bool = isempty(node.children)
 
-"""
+""" Think and choose action
 
   Arguments\n
   -----
@@ -287,7 +287,7 @@ isLeaf(node::MCTSNode)::Bool = isempty(node.children)
   Signature\n
   -----
 """
-function decisionMaker()
+function decisionMaker(state::T) where {T<:AbstractDict}
 
 end