update
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@@ -35,32 +35,27 @@ using ..type, ..util, ..llmfunction, ..mcts
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""" Think and choose action
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Arguments\n
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-----
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a::T1
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one of Yiem's agent
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state::T2
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a game state
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Return\n
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-----
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thought::Dict
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# Arguments
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`a::T1`
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one of Yiem's agent
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`state::T2`
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a game state
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# Return
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`thought::Dict`
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Example\n
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-----
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```jldoctest
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julia>
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```
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# Example
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```jldoctest
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julia>
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```
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TODO\n
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-----
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[] update docstring
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[x] implement the function
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[] implement RAG to pull similar experience
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[] use iterative prompting to ensure JSON format
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# TODO
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[] update docstring
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[x] implement the function
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[] implement RAG to pull similar experience
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[] use iterative prompting to ensure JSON format
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Signature\n
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-----
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# Signature
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"""
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function decisionMaker(a::T1, state::T2) where {T1<:agent, T2<:AbstractDict}
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customerinfo =
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@@ -134,14 +134,17 @@ function expand(a::T1, node::MCTSNode, state::T2, decisionMaker::Function, state
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# sampling action from decisionMaker
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for sample in 1:n
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thought = decisionMaker(a, state)
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thoughtJstr = decisionMaker(a, state)
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thoughtDict = copy(JSON3.read(thoughtJstr))
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latestActionKey = GeneralUtils.findHighestIndexKey(thoughtDict, "Action")
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error("--> expand")
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newState = transition(node.state, action) #[] Implement your transition function
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if newState ∉ keys(node.children)
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node.children[newState] = MCTSNode(newState, 0, 0.0, Dict{T, MCTSNode}())
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end
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end
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error("--> expand")
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end
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"""
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