This chapter proposes a framework for analysing scientific pluralism in economics using taxonomies an evolutionary approach, emphasising analogies and differences with the approach of biological evolution. It rejects Kuhn’s concept of a monolithic ‘disciplinary matrix’ dominating ‘normal science,’ arguing instead for the persistent coexistence and interaction of multiple scientific visions, even during periods of hegemonic consensus. The chapter introduces ‘epistemic matrices’ as ideal-types representing distinct scientific visions, characterized by specific assumptions about individual agents and the economic system. Three matrices are outlined: 1) (neo)classical approach, where the Homo economicus acts with unbounded rationality, generating linear dynamics with a unique stable equilibrium, applicable only to ‘closed’ worlds; 2) algorithmic behaviourism, where the Homo ‘algorithmicus’ acts with procedural rationality and learns via error correction, generating multiple attractors, irreversible time, applicable in adaptive ‘open worlds’; 3) complexity approach, where the Homo faber acts with designing rationality and proactive expectations, generating complex dynamics, applicable to evolving ‘open worlds’. It argues that while realism increases from matrix 1 to 3, formal tractability decreases. The chapter ends by sketching the ‘evolutionary tree of economic theories’, tracing the evolution of aggregate analysis from the proto macroeconomics of mercantilism and monetarism, to the New Consensus, and beyond.