The 'attainable optimum' of an agent's preferences is the most preferred option that the agent can (a) obtain using its bounded material capabilities and (b) find as an available option using its limited cognitive resources; as distinct from the theoretical global maximum of the agent's utility function. When you run a agent, what you actually get as the resulting outcome is not the single outcome that theoretically maximizes the agent's ; you rather get that agent's attainable optimum of its of that utility function. A preference framework's 'attainable optimum' is what you get in practice when somebody runs the corresponding agent.