The economic returns of cluster policies have been recently called into question. Based on a “one size fits all” approach consisting in boosting R&D collaborations and reinforcing network density, cluster policies are suspected to have failed in reaching their objectives. The paper proposes to go back to the micro foundations of clusters in order to disentangle the links between the long run performance of clusters and their structural properties. We use a simple agent-based model to shed light on how individual motives to build knowledge relationships can give rise to emerging structures with different properties, which imply different innovation and renewal capacities. The simulation results are discussed in a micro-macro perspective, and motivate suggestions to reorient cluster policy guidelines towards more targeted public-funded incentives for R&D collaboration.