Discoverers always seek the unknown. They examine the world around them, and ask: what are the boundaries that separate the known from the unknown? Then they cross the boundaries to explore the world beyond. Machine discoverers can use the same strategy. We will discuss a knowledge representation mechanism that makes it easy to find the unknown. In this representation, the current state of knowledge can be examined at any given time to find all new directions for future discovery. We can call this approach a knowledge-driven goal generation. Each state of knowledge can be transcended in different directions, so that goal generator typically creates many goals and should be followed by goal selector. In this paper we abstract from goal selection and consider only the indeterministic mechanism of goal generation.