raining rewards more heavily for moves closer to the result. Another alternative is aiming to predict an intermediate result such as the engine's own evaluation of the position following the move.</p>
        <p>Chess is a particularly difficult target for reinforcement learning and machine learning in general because <a href="https://www.aaai.org/ocs/index.php/ICAPS/ICAPS10/paper/view/1458/1571">tactical surprises appear frequently (Ramanujan, Sabharwal &amp; Selman, 2010)</a>. Making a tiny change to a po