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There is an increasing amount of research into the area of pervasive computing, smart homes and intelligent spaces, one example being that of the DTI-funded Pervasive Home Environment Networking (PHEN) project. Much of the current research focuses on environments populated by numerous computing devices, sensors, actuators, various wired and wireless networking systems and poses the question of how such computing environments might become ‘intelligent’? Often, the proposed solution is to explicitly preprogram in the intelligence. In this paper we discuss a solution based on embedded-agents which enables emergent intelligent behaviour by predominantly implicit processes. We describe an experimental test-bed for pervasive computing, the iDorm, and report on experiments that scope the agent-learning characteristics in such environments. We also introduce a more human-directed approach to programming in pervasive environments which we refer to as task-oriented programming (TOP).