BACKGROUND: Theoretical and empirical accounts of conduct disorder (CD) suggest problems with reinforcement learning as well as heightened impulsivity. These two facets can manifest in similar behaviour, such as risk-taking. Computational models that can dissociate learning from impulsively initiating actions are essential for understanding the cognitive mechanisms underlying CD. METHODS: A large, international sample of youths from 11 European countries (N = 1418, typically developing (TD) n = 742, CD n = 676) completed a learning task. We used computational modelling to disentangle reward and punishment learning from action initiation. RESULTS: Punishment learning rates were significantly reduced in youths with CD compared to their TD peers, suggesting that they did not update their actions based on punishment outcomes as strongly. Intriguingly, those with CD also had a greater tendency to initiate actions regardless of outcomes, although their ability to learn from reward was comparable to their TD peers. We additionally observed that variability in action initiation correlated with self-reported impulsivity in youths with CD. CONCLUSIONS: These findings provide empirical support for a reduced ability to learn from punishment in CD, while reward learning is typical. Our results also suggest that behaviours appearing superficially to reflect reward learning differences could reflect heightened impulsive action initiation instead. Such asymmetric learning from reward and punishment, with increased action initiation, could have important implications for tailoring learning-based interventions to help those with CD.