Emergent Behaviour

Multi-Agent System

A system composed of multiple interacting AI agents that collaborate, negotiate, or compete to solve complex problems.

Agent Swarm

A large collection of AI agents operating collaboratively using emergent behaviour patterns to solve complex tasks.

Agent Communication Language

Standardised protocols and languages used for inter-agent communication in multi-agent systems.

Agent Collaboration

The process of multiple AI agents working together, sharing information and coordinating actions to achieve common goals.

Agent Competition

A multi-agent scenario where agents pursue conflicting objectives, leading to adversarial or game-theoretic interactions.

Agent Negotiation

The process by which AI agents reach agreements through offers, counteroffers, and compromise strategies.

Safety constraints and boundaries that limit agent behaviour to prevent harmful, unintended, or out-of-scope actions.

An advanced retrieval-augmented generation pattern where an agent dynamically decides what information to retrieve, from which sources, and how to refine queries iteratively.

A meta-agent that coordinates, monitors, and manages a team of sub-agents, allocating tasks and synthesising results to fulfil complex multi-domain objectives.

An AI agent that autonomously navigates web pages, fills forms, extracts information, and completes online tasks by controlling a browser through programmatic or visual interfaces.

An agent that oversees and coordinates the work of other agents, making high-level decisions and resolving conflicts.

The ability of an AI agent to evaluate its own outputs and reasoning, identifying errors and improving responses.

An AI agent specialised in writing, debugging, refactoring, and testing software code, capable of operating across multiple files and understanding project-level context.

A business process that is partially or fully executed by autonomous AI agents rather than human workers.