  Future coalition operations can be substantially augmented through agile
teaming between human and machine agents, but in a coalition context these
agents may be unfamiliar to the human users and expected to operate in a broad
set of scenarios rather than being narrowly defined for particular purposes. In
such a setting it is essential that the human agents can rapidly build trust in
the machine agents through appropriate transparency of their behaviour, e.g.,
through explanations. The human agents are also able to bring their local
knowledge to the team, observing the situation unfolding and deciding which key
information should be communicated to the machine agents to enable them to
better account for the particular environment. In this paper we describe the
initial steps towards this human-agent knowledge fusion (HAKF) environment
through a recap of the key requirements, and an explanation of how these can be
fulfilled for an example situation. We show how HAKF has the potential to bring
value to both human and machine agents working as part of a distributed
coalition team in a complex event processing setting with uncertain sources.
