Multi-Agent on English AI Terms Dictionary

Zeuthen Strategy

Sat, 18 Jul 2026 10:20:18 +0000

Definition

The Zeuthen strategy is a rule-based approach for bargaining in multi-agent negotiations. It calculates the maximum risk an agent is willing to take to push for its preferred outcome, defined as the ratio of utility loss if agreement fails versus utility gain if the opponent concedes. Agents using this strategy will concede only when their calculated risk exceeds that of their counterpart, ensuring efficient convergence to Pareto-optimal agreements in cooperative settings.

Game theory

Sat, 18 Jul 2026 09:59:06 +0000

Definition

Game theory is a branch of applied mathematics that models strategic interactions between rational agents. It analyzes situations where the success of one player depends on the choices of others. Key concepts include Nash equilibrium, zero-sum games, and cooperative vs. non-cooperative games. In AI, it is crucial for developing multi-agent systems, reinforcement learning environments, and algorithms that must negotiate or compete with other intelligent entities.

Summary

The mathematical study of strategic interaction among rational decision-makers where outcomes depend on the actions of all participants.

Dynamic Epistemic Logic

Sat, 18 Jul 2026 09:56:08 +0000

Definition

Dynamic Epistemic Logic (DEL) extends modal logic to model how knowledge evolves when agents receive new information. It provides tools to analyze multi-agent systems where beliefs change due to public announcements, private messages, or observations. This logic is essential for designing protocols in distributed systems, verifying security properties, and modeling strategic interactions where agents must reason about each other’s knowledge and information flow.

Summary

A formal framework for reasoning about changes in agents’ knowledge states resulting from information updates or events.

Attributional Calculus

Sat, 18 Jul 2026 09:46:49 +0000

Definition

Attributional calculus is a branch of modal logic focused on reasoning about epistemic states. It provides a framework for modeling statements like ‘Agent A knows that P’ or ‘Agent B believes Q’. This is particularly relevant in multi-agent AI systems, where understanding the distinct knowledge bases and beliefs of different agents is essential for coordination, communication protocols, and resolving conflicts in shared environments.

Summary

A formal logical system used to represent and reason about knowledge attribution, specifically who knows or believes what.

Agent harness

Sat, 18 Jul 2026 09:45:08 +0000

Definition

It acts as the backbone for multi-agent systems, providing tools for orchestration, monitoring, and inter-agent coordination. The harness ensures that agents can operate efficiently without interfering with each other, handling tasks like message passing, state management, and error recovery. This abstraction allows developers to build complex applications composed of specialized agents, such as those used in automated customer service or supply chain optimization, by standardizing how agents interact with the environment and each other.

Nash

Sat, 18 Jul 2026 09:34:16 +0000

Definition

In AI, particularly in Multi-Agent Systems and Reinforcement Learning, Nash Equilibrium describes a stable state where each agent’s strategy is optimal given the strategies of all other agents. No single agent has an incentive to deviate unilaterally. This concept is crucial for training adversarial networks, designing autonomous vehicle negotiation protocols, and developing algorithms that converge to stable outcomes in competitive environments. It provides a theoretical foundation for understanding strategic interactions among rational AI agents.