Deliberative Agent

Agentic AI

AI systems that can autonomously plan, reason, and take actions to achieve goals with minimal human intervention.

AI Agent

An autonomous software entity that perceives its environment, makes decisions, and takes actions to achieve specified objectives.

Autonomous Agent

An AI agent capable of operating independently, making decisions and taking actions without continuous human oversight.

Reactive Agent

An AI agent that responds to environmental stimuli with predefined actions without maintaining an internal model of the world.

BDI Architecture

Belief-Desire-Intention — an agent architecture where agents reason about beliefs, desires, and intentions to decide actions.

Agent Planning

The ability of an AI agent to formulate a sequence of actions to achieve a goal from its current state.

Tool Use

The capability of AI agents to interact with external tools, APIs, and services to extend their functionality.

Agent Hierarchy

An organisational structure where agents are arranged in levels, with higher-level agents delegating tasks to lower-level ones.

Supervisor Agent

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

Agent Sandbox

An isolated environment where AI agents can safely execute actions and experiment without affecting production systems.

Human-on-the-Loop

A system where humans monitor AI operations and can intervene when necessary, but don't approve every action.

Agent Autonomy Level

The degree of independence an AI agent has in making and executing decisions without human approval.

The transfer of a task or conversation from one specialised AI agent to another based on skill requirements, escalation rules, or domain boundaries.

The storage mechanism enabling AI agents to retain and recall information from previous interactions and experiences.

The accumulated information, history, and environmental state that informs an AI agent's decision-making.

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

An agent architecture that interleaves reasoning traces and action steps, enabling language models to plan dynamically and use external tools to solve multi-step problems.

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

Methods and metrics for assessing the performance, reliability, and safety of autonomous AI agents.

A workflow pattern where multiple specialised agents are sequentially connected, with each agent's output feeding the next.