This paper proposes a dynamic portfolio allocation framework that integrates deep reinforcement learning (DRL) with classical portfolio optimization to enhance rebalancing strategies and risk-return management. Within a unified reinforcement-learning environment for portfolio reallocation, we...

The increasing integration of renewable energy into smart grids introduces challenges of demand-supply imbalance, peak load stress, and cyber-physical vulnerabilities. Existing demand response (DR) frameworks often lack scalability, privacy-preserving data sharing, and secure transaction...