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Evidence from empirical literature suggests that explainable complex behaviors can be built from structured compositions of explainable component behaviors with known properties. Such component behaviors can be built to directly perceive and exploit affordances. Using six examples of recent research in legged robot locomotion, we suggest that robots can be programmed to effectively exploit affordances without developing explicit internal models of them. We use a generative framework to discussdoi:10.3389/fnbot.2020.00012 pmid:32153382 pmcid:PMC7044146 fatcat:bfygsyntkrga5mcp2td5usyoau