agent-based-simulator

# Agent-Based Simulator ## Overview The Agent-Based Simulator skill provides capabilities for modeling complex adaptive systems through the simulation of heterogeneous, interacting agents. It enables bottom-up understanding of emergent market behaviors, customer dynamics, and competitive interactions for strategic decision support. ## Capabilities - Agent definition and behavior modeling - Environment and spatial modeling - Interaction rules specification - Emergent behavior observation - Parameter sweeping - Ensemble simulation runs - Visualization and animation - Statistical analysis of outcomes ## Used By Processes - War Gaming and Competitive Response Modeling - Market Sizing and Opportunity Assessment - Customer Segmentation Analysis ## Usage ### Agent Definition ```python # Define customer agent customer_agent = { "type": "Customer", "attributes": { "budget": {"distribution": "normal", "mean": 1000, "std": 200}, "brand_loyalty": {"distribution": "uniform", "min": 0, "max": 1}, "price_sensitivity": {"distribution": "beta", "alpha": 2, "beta": 5}, "preferred_features": ["list of features"] }, "behaviors": { "purchase_decision": { "triggers": ["need_arises", "promotion_seen"], "evaluation": "weighted_utility", "factors": ["price", "quality", "brand_match"] }, "word_of_mouth": { "probability": 0.3, "reach": {"distribution": "poisson", ...