<p>This study examined whether habitual video game play influences reinforcement learning dynamics, feedback adaptation, consolidation, and motivational biases. Two groups of participants (gamers and controls) completed a Probabilistic Selection Task that assessed learning from positive and negative feedback across three phases: Learning, Test, and Transfer. Mixed-effects modeling revealed that gamers showed enhanced learning trajectories, particularly under high-uncertainty conditions; however, computational modeling indicated no differences in learning rate (α), suggesting comparable value updating across groups. Gamers exhibited a higher tendency toward model-based exploitative (value-consistent) choices during learning compared to controls. In the Test phase, gamers demonstrated higher accuracy, especially on difficult stimulus pairs, suggesting more effective use of learned value representations under no-feedback conditions. This was further supported by greater model-based exploitative choices for challenging pairs. However, while no group differences emerged in transfer-phase approach/avoidance biases (VLBI), gamers showed greater decision consistency (higher inverse temperature, β) and increased exploitative choices in high-value (A-present) trials, indicating more deterministic value-guided behavior during generalization. These findings suggest that habitual video game play improves how efficiently learned values are translated into action under uncertainty, highlighting the potential of game-like environments to enhance value-guided decision-making and adaptive behavior in educational and clinical settings.</p>