random (stochastic) environment

A stochastic (random) environment is one where your actions don’t always lead to the same outcome, even if you do the exact same thing.

Analogy: Walking on Ice ❄️

Imagine you are walking on a frozen lake.

• If you take a step forward, sometimes you move forward as expected.
• But sometimes you slip left, right, or even backward due to the ice.
• The environment (ice) introduces randomness, so the same action (stepping forward) does not always give the same result.

This is different from a deterministic environment, like walking on solid ground, where every step takes you exactly where you intend.

Why It Matters in RL?

• If a robot moves in a stochastic world (e.g., on a slippery floor or in wind), it needs to learn not just actions but also their probabilities.
• RL agents in games, robotics, or stock trading must handle uncertainty because real-world actions rarely have guaranteed outcomes.