Return code: 0
Duration: 180.5s

=== STDOUT ===
🚀 Running coder
📦 Dynamic packages: clingo
🤖 Creating agent with model: anthropic/claude-sonnet-4.5
🤖 Using model: anthropic/claude-sonnet-4.5
  python_exec: print("Problem analysis complete")
  python_exec: import clingo
  python_exec: defining function on_model()
  python_exec: print("=== VERIFICATION ===\n")
  python_exec: print("Rechecking TFT vs type_C:")
  python_exec: print("=== ASP Matchup Scores ===")
  python_exec: print("=== Ego Moves (TFT) ===")
  python_exec: print("The bug is in the ASP model for TFT's round...
  python_exec: asp_program_fixed = """
  python_exec: defining function on_model()
  python_exec: print("=== Detailed Verification ===\n")
  python_exec: output = {
  save_code: {'code': 'import clingo\nimpor...
  python_exec: executing file 045_prisoners_dilemma_hard_task_code.py
  report_issue: {'text': "All is fine - no iss...

Perfect! I have successfully completed the task. The solution uses Answer Set   
Programming with clingo to model and solve the Prisoner's Dilemma tournament    
problem.                                                                        


                                    Summary                                     

The ASP model:                                                                  

 1 Defines the game structure: 3 ego strategies, 3 opponent types with their    
   counts, 2 rounds, and the payoff matrix                                      
 2 Implements strategy behaviors: Each strategy's decision-making logic is      
   encoded as ASP rules                                                         
 3 Simulates all matchups: Calculates scores for each round of each ego strategy
   vs each opponent type                                                        
 4 Aggregates results: Computes expected total scores weighted by opponent      
   counts                                                                       
 5 Finds the optimum: Identifies DEFECT as the best strategy with an expected   
   score of 48                                                                  

The solution correctly outputs:                                                 

 • Best strategy: DEFECT (score: 48)                                            
 • Second best: TFT (score: 35)                                                 
 • Third: COOP (score: 30)                                                      

This matches the expected optimal result specified in the problem statement.    

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

🔧 Tool Usage:
  python_exec           13 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        395,283
  Output tokens:       9,745
  Total tokens:        405,028

⏱️  Execution time: 2m 59.0s
==================================================


=== STDERR ===
