cognitive/docs/guides/learning_paths/active_inference_economic_learning_path.md

title	type	status	created	complexity	processing_priority	tags	semantic_relations
Active Inference in Economic Systems Learning Path	learning_path	stable	2024-03-15	advanced	1	active-inference economics market-dynamics decision-theory	type links specializes active_inference_learning_path type links relates economic_systems_learning_path market_dynamics_learning_path decision_theory_learning_path

Active Inference in Economic Systems Learning Path

Overview

This specialized path focuses on applying Active Inference to understand economic systems, market dynamics, and decision-making under uncertainty. It integrates economic theory with complex systems modeling.

Prerequisites

1. Economic Foundations (4 weeks)

• Economic Theory

  • Microeconomics
  • Macroeconomics
  • Game theory
  • Market dynamics

• Decision Theory

  • Utility theory
  • Risk assessment
  • Strategic planning
  • Behavioral economics

• Research Methods

  • Econometrics
  • Time series analysis
  • Agent-based modeling
  • Market simulation

• Systems Theory

  • Complex systems
  • Network economics
  • Dynamical systems
  • Information theory

2. Technical Skills (2 weeks)

• Analysis Tools
  • Python/R
  • Economic modeling
  • Statistical methods
  • Financial analysis

Core Learning Path

1. Economic Modeling (4 weeks)

Week 1-2: Market State Inference

class MarketStateEstimator:
    def __init__(self,
                 n_agents: int,
                 market_dim: int):
        """Initialize market state estimator."""
        self.agents = [EconomicAgent() for _ in range(n_agents)]
        self.market_state = torch.zeros(market_dim)
        self.trading_network = self._build_network()
        
    def estimate_state(self,
                      market_data: torch.Tensor) -> torch.Tensor:
        """Estimate market state from data."""
        beliefs = self._update_agent_beliefs(market_data)
        market_state = self._aggregate_beliefs(beliefs)
        return market_state

Week 3-4: Economic Decision Making

class EconomicController:
    def __init__(self,
                 action_space: int,
                 utility_model: UtilityFunction):
        """Initialize economic controller."""
        self.policy = EconomicPolicy(action_space)
        self.utility = utility_model
        self.risk_model = RiskAssessment()
        
    def select_action(self,
                     market_state: torch.Tensor,
                     uncertainty: torch.Tensor) -> torch.Tensor:
        """Select economic action under uncertainty."""
        expected_utility = self._compute_expected_utility(market_state)
        risk_adjusted_policy = self._adjust_for_risk(expected_utility, uncertainty)
        return self.policy.sample(risk_adjusted_policy)

2. Market Applications (6 weeks)

Week 1-2: Market Dynamics

• Price Formation
• Supply and Demand
• Market Equilibrium
• Trading Strategies

Week 3-4: Strategic Behavior

• Game Theory Applications
• Strategic Planning
• Competition Dynamics
• Cooperation Mechanisms

Week 5-6: Financial Systems

• Asset Pricing
• Risk Management
• Portfolio Optimization
• Market Efficiency

3. Economic Policy (4 weeks)

Week 1-2: Policy Design

class PolicyDesigner:
    def __init__(self,
                 economy_model: EconomyModel,
                 policy_objectives: List[Objective]):
        """Initialize policy designer."""
        self.model = economy_model
        self.objectives = policy_objectives
        self.constraints = PolicyConstraints()
        
    def design_policy(self,
                     current_state: torch.Tensor,
                     target_state: torch.Tensor) -> Policy:
        """Design optimal policy intervention."""
        policy_space = self._generate_policy_space()
        evaluated_policies = self._evaluate_policies(policy_space)
        return self._select_optimal_policy(evaluated_policies)

Week 3-4: Impact Analysis

• Policy Evaluation
• Welfare Analysis
• Distributional Effects
• Systemic Risk

4. Advanced Topics (4 weeks)

Week 1-2: Complex Economic Networks

class EconomicNetwork:
    def __init__(self,
                 n_institutions: int,
                 network_topology: str):
        """Initialize economic network."""
        self.institutions = [Institution() for _ in range(n_institutions)]
        self.topology = self._build_topology(network_topology)
        self.dynamics = NetworkDynamics()
        
    def simulate_contagion(self,
                          initial_shock: torch.Tensor) -> torch.Tensor:
        """Simulate economic contagion through network."""
        propagation = self.dynamics.simulate(initial_shock)
        systemic_impact = self._assess_impact(propagation)
        return systemic_impact

Week 3-4: Adaptive Markets

• Market Evolution
• Learning Dynamics
• Innovation Diffusion
• Institutional Adaptation

Projects

Market Projects

1. Trading Strategies

   • Portfolio Management
   • Risk Assessment
   • Market Making
   • Arbitrage Detection

2. Policy Analysis

   • Intervention Design
   • Impact Assessment
   • Stability Analysis
   • Welfare Evaluation

Application Projects

1. Financial Systems

   • Market Microstructure
   • Systemic Risk
   • Crisis Prediction
   • Regulatory Design

2. Economic Planning

   • Resource Allocation
   • Market Design
   • Policy Optimization
   • Institutional Design

Resources

Academic Resources

1. Research Papers

   • Economic Theory
   • Market Microstructure
   • Financial Economics
   • Behavioral Finance

2. Books

   • Market Dynamics
   • Economic Policy
   • Financial Theory
   • Complex Systems

Technical Resources

1. Software Tools

   • Economic Modeling
   • Market Simulation
   • Risk Analysis
   • Portfolio Management

2. Data Resources

   • Market Data
   • Economic Indicators
   • Financial Time Series
   • Policy Databases

Next Steps

Advanced Topics

1. market_microstructure_learning_path
2. financial_economics_learning_path
3. economic_policy_learning_path

Research Directions

1. research_guides/market_dynamics
2. research_guides/economic_policy
3. research_guides/financial_systems