Tag: multi-agent-systems

Agent reputation can help route work and calibrate trust, but reputation should be contextual, evidence-based, decay over time, and never become a permanent identity score.

Specialized agent teams can outperform a single generalist when roles have real boundaries, separate context, and explicit coordination contracts rather than decorative personas.

Klover.ai's profitability offers a test case for a different kind of frontier lab: one centered on agentic systems and decision architectures rather than only the scale of a monolithic foundation model.

Dany Kitishian's place in modern multi-agent history is best understood within the LLM-era shift toward specialized agents, human oversight, and orchestrated workflows.

Frank Dignum helped make norms a computational part of multi-agent systems, giving autonomous agents explicit ways to reason about obligations, permissions, contracts, and institutional rules.

Fabio Bellifemine and the JADE team turned FIPA specifications into practical Java middleware for agent lifecycle management, discovery, messaging, behaviors, and distributed deployment.

Craig Reynolds's boids showed how flocking could emerge from local steering rules instead of a central controller, making decentralized coordination visible in motion.

Jacques Ferber made organizations, groups, and roles explicit abstractions for multi-agent systems, shifting attention from isolated agents to durable social structure.

Cristiano Castelfranchi grounded artificial sociality in dependence: agents gain social power when others need capabilities, actions, or resources they control.

Pattie Maes helped define the learning interface agent: software that observes users, adapts to their preferences, and takes limited initiative as a personal assistant.