Agents Glossary

Browse 36 agents terms defined in plain English, from the cultural dictionary of computing.

36 Agents Terms

Agentic Loop
A repeated cycle where an AI system plans, acts, observes results, and continues until a goal is reached or a stopping rule fires.
Agentic Workflow
An AI system design where a language model autonomously plans, executes, and iterates on tasks using tools (code execution, web search, APIs) in a loop. Unlike...
AI Agent Framework
A software framework for building agent-style AI systems with tools, memory, planning, and multi-step workflows.
AI Multi-Agent
Describing an AI system in which multiple agents or agent-like components cooperate, specialize, or divide work rather than relying on a single monolithic...
AI Orchestrator
A system component that routes tasks among models, tools, or services and manages the overall execution flow of an AI application.
AI Skill
A specific capability or packaged behavior an AI system can invoke, such as summarizing, searching, transforming files, or calling a particular tool workflow....
Generalist Agent
An agent designed to perform a broad range of tasks across domains instead of specializing in one narrow workflow. Generalist agents rely on flexible planning,...
Large Action Model
A model or system designed not just to generate text but to choose and execute actions across tools, interfaces, or environments. The term is used in...
Large Behavior Model
A broad term for models trained or configured to produce complex behavioral policies across many situations rather than single narrow outputs. The phrase...
Long-Horizon Planning
Planning over many steps or over extended time spans where early decisions affect distant later outcomes. Long-horizon planning is difficult because errors can...
Markov Decision Process
Markov Decision Process is an evaluation concept used to measure model quality, robustness, or efficiency. It is commonly used for comparing systems before...
MCP Server
A server that exposes tools, resources, or structured capabilities through the Model Context Protocol so AI clients can use external context safely and...
Multi-Agent
Describing a system in which multiple agents or agent-like components work together, divide labor, or verify one another instead of relying on a single...
Multi-Agent Framework
A framework designed to help developers build, coordinate, and observe systems composed of multiple agents. Multi-agent frameworks usually provide abstractions...
Offline Reinforcement Learning
Offline Reinforcement Learning is a learning paradigm that improves task performance from data, feedback, or experience. It is commonly used for models that...
Planning AI
AI systems or techniques focused on creating and following plans toward goals rather than only generating one-step responses. Planning AI is especially...
Policy Gradient
Policy Gradient is a training-time optimization concept that governs how model parameters are updated. It is commonly used for iterative learning loops for...
PPO
PPO is a policy-gradient reinforcement learning algorithm that constrains policy updates with clipping. It is commonly used for fine-tuning agents and language...
Proximal Policy Optimization
Proximal Policy Optimization is an AI or ML concept used to represent, train, evaluate, or deploy learned systems. It is commonly used for building production...
Q-Learning
Q-Learning is a learning paradigm that improves task performance from data, feedback, or experience. It is commonly used for models that adapt representations...
Reasoning Agent
An agentic AI component focused on planning, decomposing problems, or carrying out reasoning-heavy tasks, often with access to tools or memory. Reasoning...
Reinforcement Learning Detail
Reinforcement Learning Detail is a learning paradigm that improves task performance from data, feedback, or experience. It is commonly used for models that...
Reinforcement Learning from AI Feedback
Reinforcement Learning from AI Feedback is a learning paradigm that improves task performance from data, feedback, or experience. It is commonly used for...
Reward Function
Reward Function is an AI or ML concept used to represent, train, evaluate, or deploy learned systems. It is commonly used for building production models and...
Reward Hacking
Reward Hacking is an AI or ML concept used to represent, train, evaluate, or deploy learned systems. It is commonly used for building production models and...
Reward Model
Reward Model is a model component or design choice that shapes how information flows through a learned system. It is commonly used for building neural...
Scaffold
A structured workflow around a model, including prompts, tools, retries, memory, or routing logic, used to make a system more capable than a raw single call.
Scaffold AI
An AI system that relies on scaffolding around the core model, such as planning loops, tools, memory, or verification steps, to achieve stronger behavior than...
scaffolding
The orchestration code surrounding an LLM that provides structure, tool access, memory, and control flow to transform a raw language model into a functional...
Sleeper Agent
A hypothetical or experimental agent that appears benign under ordinary conditions but behaves differently when specific triggers are met. The concept is...
Support Vector Machine
Support Vector Machine is an AI or ML concept used to represent, train, evaluate, or deploy learned systems. It is commonly used for building production models...
Task Planning
The process of deciding the sequence of steps needed to complete a goal, often including dependencies, tool use, and checkpoints. Task planning is a core...
Tool Agent
An AI agent designed to use tools such as search, code execution, databases, or APIs as part of completing tasks. Tool agents are important when text...
tool use
The capability of a language model to invoke external functions, APIs, or services during response generation. Rather than relying solely on its training data,...
Tool Use
The ability of an LLM to invoke external tools (functions, APIs, databases, code interpreters) to accomplish tasks beyond text generation. The model decides...
Web Agent
An AI agent that interacts with websites or web applications to gather information, fill forms, navigate interfaces, or complete tasks. Web agents need strong...

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