People often choose immediate certain outcomes over delayed uncertain ones, even when the latter are more beneficial. This suggests that delay and uncertainty diminish the perceived value of a reward - a phenomenon known as delayed probabilistic discounting (DPD). Studying discounting mechanisms is critical to understand behavior in various life domains including finance, health, and relationships [1]. However, delayed and probabilistic discounting processes are usually studied independently. It is therefore unclear whether choices that involve both processes are simply a product of the individual processes or whether their combination generates qualitatively distinct cognitive and behavioral phenomena. Addressing this question is challenging due to significant interindividual variability in discounting patterns [2]. Here, we aimed to design an experimental framework to investigate whether cognitive processes underlying DPD differ from those in simple delay discounting (DD) and probability discounting (PD) [3, 4]. Based on prior work [5,6], our paradigm consists of 2 experimental runs: in the first run, we acquire behavioral discounting data on a DPD task. The run is guided by model-based active learning principles [7] and serves to infer individual-level behavioral discounting models used to adapt the second run. In the second run, the inferred models are utilized to generate adaptive discounting trials consisting either of DPD, or separate DD and PD trials. The generated trials are designed to induce graded levels of immediate certain choice frequencies. We hypothesize that if DPD is merely a product of DD and PD processes, model-based predictions between the combined condition and the separate DD and PD condition will be identical. First, we demonstrate that our paradigm successfully induces graded choice frequencies, indicating a robust and valid experimental design. Second, our preliminary analyses show that behavioral models derived from a joint DPD task yield qualitatively different predictions when evaluated on a joint DPD task compared to isolated DD and PD tasks. Notably, the predictions for DD are not well-aligned with those for DPD, suggesting that DD is not adequately considered during DPD tasks. This implies that DPD processes encompass more than just the combination of their parts. Lastly, the established paradigm can be used to homogenize behavior for studying the neuroscientific correlates of discounting on a dimensional level.