  We consider the problem of exploring an unknown tree with a team of $k$
initially colocated mobile agents. Each agent has limited energy and cannot, as
a result, traverse more than $B$ edges. The goal is to maximize the number of
nodes collectively visited by all agents during the execution. Initially, the
agents have no knowledge about the structure of the tree, but they gradually
discover the topology as they traverse new edges. We assume that the agents can
communicate with each other at arbitrary distances. Therefore the knowledge
obtained by one agent after traversing an edge is instantaneously transmitted
to the other agents. We propose an algorithm that divides the tree into
subtrees during the exploration process and makes a careful trade-off between
breadth-first and depth-first exploration. We show that our algorithm is
3-competitive compared to an optimal solution that we could obtain if we knew
the map of the tree in advance. While it is easy to see that no algorithm can
be better than 2-competitive, we give a non-trivial lower bound of 2.17 on the
competitive ratio of any online algorithm.
