state-thoughts

name	state-thoughts
title	STATe-of-Thoughts: Structured Action Templates for Tree-of-Thoughts
version	0.0.2
engine	skillxiv-v0.0.2-claude-opus-4.6
license	MIT
url	https://arxiv.org/abs/2602.14265
keywords	["Chain-of-Thought","Tree-of-Thoughts","Structured Reasoning","Action Templates","Problem Solving"]
description	Guide multi-step reasoning through structured action templates that decompose problems into discrete, executable steps. STATe improves exploration efficiency in tree-of-thoughts by constraining action space while maintaining reasoning flexibility.

STATe-of-Thoughts: Structured Action Templates for Reasoning

Problem Context

Tree-of-Thoughts (ToT) explores reasoning paths by considering multiple next steps at each node. However, without structure, the action space becomes enormous, making it expensive to explore deeply. Standard ToT generates free-form text for next steps, causing:

1. Redundant exploration: Similar reasoning attempted multiple ways
2. Invalid continuations: Actions incompatible with problem structure
3. High token cost: Sampling many candidate actions
4. Poor tree efficiency: Wide but shallow vs deep exploration

Core Concept

STATe-of-Thoughts introduces structured action templates that decompose problem-solving into discrete, templated steps. Rather than free-form generation, each reasoning step must fit a predefined action template appropriate to the problem domain. Templates constrain the action space (reducing exploration breadth) while maintaining flexibility in reasoning content.

The key insight: structure doesn't reduce reasoning power—it focuses exploration on relevant actions, improving tree depth and solution quality while reducing token cost.

Architecture Overview

• Action Template Library: Domain-specific templates for problem types
• Template-Based Action Generation: Fill-in-the-blank structure
• Valid Action Filtering: Only valid template instances in tree
• Step-Wise Decomposition: Each node has discrete, structured actions
• Template Selection Policy: Choose appropriate template per state
• Efficiency Metrics: Reduced tokens while maintaining or improving solution quality
• Domain Specialization: Custom templates for math, code, planning, etc.

Implementation

Action template system:

class ActionTemplateLibrary:
    """
    Structured action templates for different problem types.
    Templates constrain action space while maintaining flexibility.
    """

    def __init__(self):
        self.templates = {
            'math_problem': [
                'Identify what we know: {facts}',
                ,
                ,
                ,
                ,
                ,
                ,
                
            ],
            : [
                ,
                ,
                ,
                ,
                ,
                ,
                ,
                
            ],
            : [
                ,
                ,
                ,
                ,
                ,
                ,
                ,
                
            ],
            : [
                ,
                ,
                ,
                ,
                ,
                ,
                ,
                
            ]
        }

     ():
        
         .templates.get(problem_type, [])

     ():
        
        action = template
         key, value  kwargs.items():
            action = action.replace(, (value))
         action