Agents are language models which are given persistent access to tooling and memory in order to solve an open-ended task. Agents might be given access to third-party APIs, code interpreters, or a scratch pad to record previously generated texts and told to use them when appropriate in order to complete a task. An agent operates autonomously (not directly controlled by a human operator).

Image credits: Z. Xi et al,

There are a number of types of agents within machine learning:

     1) Reactive: an agent responds to stimuli from their environment to achieve goal

     2) Proactive: an agent takes initiative and plans in advance to achieve goal

     3) Operate in a fixed environment: contain a static set of rules in which an agent should respond

     4) Operate in a dynamic environment: rules are constantly changing and it therefore requires an agent to regularly adapt to new circumstances

     5) Single agent: as described

     6) Multi-agent system: where many agents work together to achieve a common goal

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