Which one is NOT a function of a model-based agent?

A model-based agent is designed to utilize an internal model of its environment to make informed decisions and take actions. It accomplishes this through various functions that enhance its ability to operate effectively over time.

One key function is updating its internal representation over time, which allows the agent to adapt to changes in its environment. This continual updating is crucial for maintaining accuracy in decision-making. Additionally, by applying rules based on perceptions, the agent can act in a way that aligns with its understanding of the current state of its environment, using the most recent data available to inform its actions.

Maintaining a perception history is also essential for a model-based agent. This historical data helps the agent make better predictions and decisions by providing context for current perceptions and actions.

Acting based on an outdated model, however, goes against the core objective of a model-based agent. Such behavior would lead to ineffective or erroneous actions, as the agent would not be aligned with the present state of the environment. Thus, this option accurately highlights a practice that is not characteristic of an effective model-based agent.