update

src/interface.jl

@@ -85,10 +85,11 @@ function runMCTS(
       # do nothing then go directly to backpropagation. It means the end of this iteration
       backpropagate(node, node.reward)
     else
+      println(111)
       _ = expand(node, transition, transitionargs;
                 horizontalSample=horizontalSampleExpansionPhase)
 
-      println(555)
+      println(666)
       
       @sync for (leafNodeKey, leafNode) in node.children
         @spawn simulateThenBackpropagate(leafNode, transition, transitionargs;
@@ -96,6 +97,14 @@ function runMCTS(
                 horizontalSampleSimulationPhase=horizontalSampleSimulationPhase,
                 saveSimulatedNode=saveSimulatedNode)
       end
+
+      #CHANGE for testing
+      # for (leafNodeKey, leafNode) in node.children
+      #   simulateThenBackpropagate(leafNode, transition, transitionargs;
+      #           maxSimulationDepth=maxSimulationDepth, 
+      #           horizontalSampleSimulationPhase=horizontalSampleSimulationPhase,
+      #           saveSimulatedNode=saveSimulatedNode)
+      # end
     end
 
     # stop if the early stop condition is met

src/mcts.jl

@@ -198,68 +198,67 @@ end
 
 # Signature
 """
-# function expand(node::MCTSNode, transition::Function, transitionargs::NamedTuple; 
-#           totalsample::Integer=3)
+function expand(node::MCTSNode,transition::Function, transitionargs::NamedTuple; 
+                horizontalSample::Integer=3)
+  @sync for i in 1:horizontalSample 
+    @spawn _expand(node, transition, transitionargs)
+  end
   
-#   # not use Any[] because I want to preserve result order
-#   results = Vector{Any}(undef, totalsample) 
+  #CHANGE for testing
+  # for i in 1:horizontalSample
+  #   _expand(node, transition, transitionargs)
+  # end
+end
+# function expand(node::MCTSNode,transition::Function, transitionargs::NamedTuple; 
+#                 horizontalSample::Integer=3)
 
-#   @sync for i in 1:totalsample
-#       @spawn begin
-#         result = transition(deepcopy(node.state), deepcopy(transitionargs))
-#         results[i] = result
+#   nthSample = 0
+#   listOfNewNodeId = []
+#   while true
+#     nthSample += 1
+#     if nthSample <= horizontalSample
+#       result = transition(node.state, transitionargs)
+#       newNodeKey::AbstractString = result[:newNodeKey]
+#       newstate::AbstractDict = result[:newstate]
+#       progressvalue::Integer = result[:progressvalue]
+
+#       """
+#       [] newNodeKey ∉ keys(node.children). 
+#             New state may have semantic vector close enought to 
+#           one of existing child state. Which can be assume that they are the same state 
+#           semantically-wise i.e. De javu. This could be used to recall lessons for this 
+#           similar situation to improve decisionMaker and evaluator. 
+#       """
+#       if newNodeKey ∉ keys(node.children)
+#         push!(listOfNewNodeId, newNodeKey)
+#         newNode = MCTSNode(newNodeKey, newstate, 0, progressvalue, 0, newstate[:reward], 
+#             newstate[:isterminal], node, Dict{String, MCTSNode}(), Dict{Symbol, Any}())
+#         node.children[newNodeKey] = newNode
 #       end
-#   end
-  
-#   for result in results
-#     newNodeKey::AbstractString = result[:newNodeKey]
-#     newstate::AbstractDict = result[:newstate]
-#     progressvalue::Integer = result[:progressvalue]
-
-#     """
-#     [] newNodeKey ∉ keys(node.children). 
-#           New state may have semantic vector close enought to 
-#         one of existing child state. Which can be assume that they are the same state 
-#         semantically-wise i.e. De javu. This could be used to recall lessons for this 
-#         similar situation to improve decisionMaker and evaluator. 
-#     """
-#     if newNodeKey ∉ keys(node.children)
-#       node.children[newNodeKey] = 
-#         MCTSNode(newNodeKey, newstate, 0, progressvalue, 0, newstate[:reward], 
-#           newstate[:isterminal], node, Dict{String, MCTSNode}())
+#     else
+#       return listOfNewNodeId
 #     end
 #   end
 # end
-function expand(node::MCTSNode,transition::Function, transitionargs::NamedTuple; 
-                horizontalSample::Integer=3)
 
-  nthSample = 0
-  listOfNewNodeId = []
-  while true
-    nthSample += 1
-    if nthSample <= horizontalSample
-      result = transition(node.state, transitionargs)
-      newNodeKey::AbstractString = result[:newNodeKey]
-      newstate::AbstractDict = result[:newstate]
-      progressvalue::Integer = result[:progressvalue]
+function _expand(node::MCTSNode,transition::Function, transitionargs::NamedTuple)
+    result = transition(node.state, transitionargs)
+    newNodeKey::AbstractString = result[:newNodeKey]
+    newstate::AbstractDict = result[:newstate]
+    progressvalue::Integer = result[:progressvalue]
 
-      """
-      [] newNodeKey ∉ keys(node.children). 
-            New state may have semantic vector close enought to 
-          one of existing child state. Which can be assume that they are the same state 
-          semantically-wise i.e. De javu. This could be used to recall lessons for this 
-          similar situation to improve decisionMaker and evaluator. 
-      """
-      if newNodeKey ∉ keys(node.children)
-        push!(listOfNewNodeId, newNodeKey)
-        newNode = MCTSNode(newNodeKey, newstate, 0, progressvalue, 0, newstate[:reward], 
-            newstate[:isterminal], node, Dict{String, MCTSNode}(), Dict{Symbol, Any}())
-        node.children[newNodeKey] = newNode
-      end
-    else
-      return listOfNewNodeId
+    """
+    [] newNodeKey ∉ keys(node.children). 
+          New state may have semantic vector close enought to 
+        one of existing child state. Which can be assume that they are the same state 
+        semantically-wise i.e. De javu. This could be used to recall lessons for this 
+        similar situation to improve decisionMaker and evaluator. 
+    """
+    if newNodeKey ∉ keys(node.children)
+      newNode = MCTSNode(newNodeKey, newstate, 0, progressvalue, 0, newstate[:reward], 
+          newstate[:isterminal], node, Dict{String, MCTSNode}(), Dict{Symbol, Any}())
+      node.children[newNodeKey] = newNode
     end
-  end
 end