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Eden, explain the causal_inference_engine_1765521341 capability
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This capability handles Counterfactual reasoning and intervention planning. Here's the implementation:

```python
import json
import logging
from datetime import datetime
from typing import Dict, List, Optional, Any

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

class CausalInferenceEngine:
    """
    A module for causal inference and counterfactual reasoning.
    
    Attributes:
        interventions: Dictionary of possible interventions and their effects
        outcomes: History of computed outcomes
    """

    def __init__(self):
        self.interventions: Dict[str, Dict] = {}
        self.outcomes: List[Dict] = []
        
    def add_intervention(self, intervention_id: str, effect_size: float, 
                        control_group: bool = False) -> None:
        """
        Add a possible intervention.
        
        Args:
            intervention_id: Unique identifier for the intervention
            effect_size: Expected effect size on outcome variable
            control_group: Whether this is a control group (default: False)
        """
        self.interventions[intervention_id] = {
            'id': intervention_id,
            'effect_size': effect_size,
            'control_group': control_group,
            'timestamp': datetime.now().isoformat()
        }
        logger.info(f"Added intervention {intervention_id} with effect size {effect_size}")
        
    def simulate_experiment(self, treatment_group: str, outcome_var: str) -> Dict:
        """
        Simulate an experiment to estimate causal effect.
        
        Args:
            treatment_group: ID of the treatment group
            outcome_var: Name of the outcome variable
            
        Returns:
            Dictionary with estimated causal effect and counterfactual outcomes
        """
        try:
            control_group = next(g for g in self.interventions.values() if not g['control_group'])
            original_outcome_treatment = self._get_data(outcome_var, treatment_group)
            original_outcome_control = self._get_data(out
```

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