We present autonomous agents that are designed without encoding strategies or knowledge of the environment in the agent. The design approach focuses on the notion of sensorimotor patterns of interaction between the agent and the environment rather than separating perception from action. The agent’s motivational system is also interaction-centered in that the agent has inborn proclivities to enact certain sensorimotor patterns and to avoid others. Such motivations result in the agent autonomously discovering, learning, and exploiting regularities of interaction afforded by the environment, and constructing operative knowledge of the environment. Because such agents have no predefined goals, we propose a set of behavioral criteria to both judge and demonstrate the agents’ capacities, rather than performance measurement. A design platform based on NetLogo is presented. Results show that these agents demonstrate interesting behavioral properties such as hedonistic temperance, active perception, and individuation.