What is a Markov property?
A property of certain environments, where state transitions are entirely determined by information implicit in the current state and the agent's action.
Markov property explained in plain English
Example
Practitioners refer to markov property when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.
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A stage in the agentic loop in which the agent executes the action chosen during the reason stage.
- action
In reinforcement learning, the mechanism by which the agent transitions between states of the environment.
- action space
The set of resources an agent can use to perform a task.
- Agent
An AI system that can perceive its environment, make decisions, and take actions to achieve goals autonomously.
- agent orchestration
The centralized management and routing of tasks across multiple sub-agents or LLM calls.
- agentic
The adjective form of agent.
- agentic loop
A cycle that an agent iterates through until a termination condition is met.
- agentic workflow
A dynamic process in which an agent autonomously plans and executes actions to achieve a goal.
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An agent that works towards a complex goal by planning, acting, and adapting without continuous human intervention.
- environment
In reinforcement learning, the world that contains the agent and allows the agent to observe that world's state.