def monteCarloEstimation()

in 1_synthetic-qa-generation/reasoningplaning/evolve.py [0:0]
33 lines of code
13 McCabe index (conditional complexity)

    def monteCarloEstimation(self, node: Nde):
        numTrueBranches = 0  # Correct branches count
        falseBranches = []
        trueBranches = []
        genBranches = self.branchMaker.generateBranch(node.solution_prefix, self.numBranches)

        node.numVisited += 1

        for i, branch in enumerate(genBranches):
            if branch is None or not branch:
                continue
            self.numOfTtlBranches += 1

            # Generate branch r_i
            node.addBranch(branch)

            # Evaluate correctness of final answer in branch
            fullSolution = (node.solution_prefix + '\n\n' + branch).strip() if node.solution_prefix else branch
            isCorrect = self.branchMaker.evaluateCorrectness(fullSolution, self.expected_answer)

            if isCorrect:
                numTrueBranches += 1
                trueBranches.append(branch)
            else:
                falseBranches.append(branch)
                node.addFalseBranch(branch)  # Track incorrect branches

        # Update total branches and correct branches
        node.numOfTtlBranches += self.numBranches
        node.trueBranches += numTrueBranches
        node.reward = node.trueBranches / node.numOfTtlBranches if node.numOfTtlBranches > 0 else 0

        # logger.info(f"Monte Carlo Estimation for Nde ID {self.mct.nodes.index(node)}: reward = {node.reward:.2f}, Total Rollouts = {node.numOfTtlBranches}, Correct Rollouts = {node.trueBranches}\n")

        if node.reward == 1.0:
            # Add all correct branches to the tree as new states
            for branch in trueBranches:
                self.addTrueBranch2Tree(node, branch)
        elif node.reward == 0.0:
            # Nde is incorrect; no further action
            return
        else:
            # 0 < reward(s) < 1.0
            # Add correct branches to the tree
            for branch in trueBranches:
                self.addTrueBranch2Tree(node, branch)
            # Add incorrect branches to candidate pool with updated priorities
            for branch in falseBranches:
                priority = self.computeSelectionScore(node, branch)
                self.candidatePool.addOrUpdate(node, branch, priority)