Return code: 0
Duration: 78.9s

=== STDOUT ===
🚀 Running coder
📦 Dynamic packages: clingo
🤖 Creating agent with model: anthropic/claude-sonnet-4.5
🤖 Using model: anthropic/claude-sonnet-4.5
  python_exec: defining function create_asp_program()
  python_exec: defining function solve_independent_dominating_set()
  python_exec: dominating_set = [4, 9, 14, 17]
  save_code: {'code': 'import clingo\nimpor...
  report_issue: {'text': 'All is fine - no iss...


                                    Summary                                     

I've successfully completed the independent dominating set problem using Answer 
Set Programming with clingo. The solution:                                      

Result:                                                                         

                                                                                
 {                                                                              
   "dominating_set": [4, 9, 14, 17],                                            
   "total_cost": 10                                                             
 }                                                                              
                                                                                

Key Features of the ASP Model:                                                  

 1 Independent Set Constraint: Forbids any two adjacent vertices from being in  
   the dominating set                                                           
 2 Type-Specific Domination Rules:                                              
    • Critical vertices: Need ≥1 neighbor in the set                            
    • Standard vertices: Need ≥1 neighbor in the set                            
    • Resilient vertices: Need ≥2 neighbors in the set                          
 3 Cost Optimization: Uses #minimize to find the minimum-cost solution          
 4 Aggregate Counting: Uses #count to verify each vertex has sufficient         
   neighbors in the dominating set                                              

The solution was verified to satisfy all constraints and achieves the expected  
minimum cost of 10.                                                             

==================================================
📊 Execution Statistics
==================================================

🔧 Tool Usage:
  python_exec            3 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        68,863
  Output tokens:       4,778
  Total tokens:        73,641

⏱️  Execution time: 1m 18.0s
==================================================


=== STDERR ===
