Reinforcement learning

Termination and truncation

Termination means the task reached an end state. Truncation means an external limit stopped observation, even if the underlying task could continue.

Ask the Reinforcement learning assistant 1 min read · Updated September 9, 2026

Definition

Termination means the task reached an end state. Truncation means an external limit stopped observation, even if the underlying task could continue.

Intuition

Running out of test time is different from reaching the goal. Confusing them changes the value target.

Worked example

A robot reaches its destination: termination. A simulator stops after 200 steps while the robot is moving: truncation.

The math

For a genuine terminal state, the next-state value is zero. Time-limit truncation may still require bootstrapping when the task continues.

In practice

Store both flags in a replay buffer and test the target for each case. Use the environment semantics to decide whether the horizon is part of the task.

Go deeper

Sources

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