Multi-agent artificial intelligence (MAAI) represents a foundational shift in the automation of knowledge work, moving beyond static workflows toward adaptive systems of interacting AI-based agents. These agents perceive, reason, and coordinate in real time to address complex, context-rich tasks...

In response to the challenges posed by an increasingly decentralized energy system characterized by a high penetration of renewable energy sources, grid operators are experiencing heightened pressure to effectively manage grid congestion. Concurrently, both the European Union as well as the...

Background: Intralogistics systems face growing challenges from globalization, individualization, and shorter product life cycles, demanding flexible and responsive solutions beyond traditional centralized control. Decentralized, agent-based approaches offer potential advantages, especially for...

In response to the challenges posed by an increasingly decentralized energy system characterized by a high penetration of renewable energy sources, grid operators are experiencing heightened pressure to effectively manage grid congestion. Concurrently, both the European Union as well as the...

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...

This study proposes an absolute and relative performance evaluation (ARPE) framework integrating both objective (group size) and subjective (competition concern) incentives. In homogeneous settings, moderate competition increases effort and payoff, whereas excessive competition distorts...