The maturation of reaction exploration algorithms will provide access to chemical network kinetics during the chemical discovery and design phases, rather than retrospectively. This presents several exciting possibilities for catalyst design, including optimizing catalysts with respect to specific products rather than specific mechanisms, predicting off-target pathways, and generating hypotheses for novel catalytic cycles. Here we have demonstrated how automatic exploration can be applied to heterogeneous catalytic networks using ethylene oligomerization catalyzed by a silica-supported Ga single site as a benchmark. The method (re)discovered the classic Cossee-Arlman oligomerization cycle and several side-product pathways with minimal user intervention. Given the generic reaction rules and size constraints that were used to generate this network, there are relatively few obstacles to applying this approach to other heterogeneous systems. Among the salient details of the implementation to consider moving forward are the use of a cluster model as a surrogate for a periodic slab and the major speedup provided by semi-empirical quantum chemistry. Neither detail is intrinsic to applying YARP. The cluster assumption was validated here and adopted out of convenience, since the useful GFN2-XTB semi-empirical method is at present non-periodic. There are no obstacles to applying YARP using a periodic code, outside of cost. Notably, cluster models used to be much more prevalent before the adoption of periodic DFT, and as demonstrated here, the assumption is robust for establishing relative barriers in localized catalysts, like oxide surfaces, that can be refined later at the periodic level as required. The applicability of this approach to other heterogeneous surfaces is therefore anticipated and is currently under investigation.