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+# Multi-step Reasoning - MCTS with Chain of Thought
+
+This example demonstrates MCTS for multi-step reasoning problems, where the LLM generates chain-of-thought reasoning at each step.
+
+```julia
+using LLMMCTS
+
+# State tracks the reasoning process
+# thought_history: Dict mapping thought/action keys to their content
+
+function reasoning_transition(state::Dict, args::NamedTuple)
+    current_step = get(state, :step, 0)
+    thought_history = get(state, :thought_history, Dict{String, String}())
+    problem = state[:problem]
+    
+    if current_step == 0
+        # Step 1: Understand the problem
+        thought = "First, I need to understand what the problem is asking. The problem requires me to analyze the given information and determine the solution approach."
+        action = "Identify the key components of the problem"
+        
+        new_thought_history = copy(thought_history)
+        new_thought_history["thought_1"] = thought
+        new_thought_history["action_1"] = action
+        
+        newstate = Dict(
+            :step => 1,
+            :thought_history => new_thought_history,
+            :reward => 1.0,
+            :isterminal => false
+        )
+        progressvalue = 3.0
+    elseif current_step == 1
+        # Step 2: Break down the problem
+        thought = "Next, I should break this down into smaller sub-problems. This will make it easier to solve step by step."
+        action = "Divide the problem into manageable parts"
+        
+        new_thought_history = copy(thought_history)
+        new_thought_history["thought_2"] = thought
+        new_thought_history["action_2"] = action
+        
+        newstate = Dict(
+            :step => 2,
+            :thought_history => new_thought_history,
+            :reward => 2.0,
+            :isterminal => false
+        )
+        progressvalue = 5.0
+    elseif current_step == 2
+        # Step 3: Solve each sub-problem
+        thought = "Now I'll solve each sub-problem individually, using appropriate methods for each."
+        action = "Apply solution methods to each sub-problem"
+        
+        new_thought_history = copy(thought_history)
+        new_thought_history["thought_3"] = thought
+        new_thought_history["action_3"] = action
+        
+        newstate = Dict(
+            :step => 3,
+            :thought_history => new_thought_history,
+            :reward => 3.0,
+            :isterminal => false
+        )
+        progressvalue = 7.0
+    elseif current_step == 3
+        # Step 4: Combine solutions
+        thought = "Finally, I'll combine all the solutions to form the complete answer to the original problem."
+        action = "Integrate solutions and verify the answer"
+        
+        new_thought_history = copy(thought_history)
+        new_thought_history["thought_4"] = thought
+        new_thought_history["action_4"] = action
+        
+        newstate = Dict(
+            :step => 4,
+            :thought_history => new_thought_history,
+            :reward => 4.0,
+            :isterminal => true  # Reasoning complete
+        )
+        progressvalue = 10.0
+    else
+        newstate = Dict(
+            :step => current_step,
+            :thought_history => thought_history,
+            :reward => 10.0,
+            :isterminal => true
+        )
+        progressvalue = 10.0
+    end
+    
+    return Dict(
+        :newNodeKey => "reasoning_step_$current_step",
+        :newstate => newstate,
+        :progressvalue => progressvalue
+    )
+end
+
+# Initial state
+initialstate = Dict(
+    :step => 0,
+    :problem => "Explain how photosynthesis works",
+    :thought_history => Dict{String, String}(),
+    :reward => 0,
+    :isterminal => false
+)
+
+# Transition arguments
+transitionargs = (max_steps = 4,)
+
+# Run MCTS
+result = runMCTS(
+    initialstate,
+    reasoning_transition,
+    transitionargs;
+    maxiterations = 25,
+    explorationweight = 1.0,
+    maxSimulationDepth = 4,
+    horizontalSampleExpansionPhase = 3
+)
+
+# Display results
+println("Multi-step Reasoning Example")
+println("=============================")
+println()
+println("Problem: ", initialstate[:problem])
+println()
+println("Reasoning steps:")
+for (key, value) in result.bestTerminalState[:thought_history]
+    println("  $key: $value")
+end
+println()
+println("Reasoning complete! ✓")
+println("Root node visits: ", result.root.visits)
+println("Total steps in reasoning chain: ", result.bestTerminalState[:step])
+```