An important ability of self-adaptive systems is to be able to autonomously understand the environment in which they operate and use this knowledge to control the environment behaviour in such a way that system goals are achieved. How can this be achieved when the environment is unknown? Two phase solutions that require a full discovery of environment behaviour before computing a strategy that can guarantee the goals or report the non-existence of such a strategy (i.e., unrealisability) are impractical as the environment may exhibit adversarial behaviour to avoid full discovery. In this paper we formalise a control and discovery problem for reactive system environments. In our approach a strategy must be produced that will, for every environment, guarantee that unrealisablity will be correctly concluded or system goals will be achieved by controlling the environment behaviour. We present a solution applicable to environments characterisable as labeled transition systems (LTS). We use modal transition systems (MTS) to represent partial knowledge of environment behaviour, and rely on MTS controller synthesis to make exploration decisions. Each decision either contributes more knowledge about the environment's behaviour or contributes to achieving the system goals. We present an implementation restricted to GR(1) goals and show its viability.