  We study the problem of multi-agent online graph exploration, in which a team
of k agents has to explore a given graph, starting and ending on the same node.
The graph is initially unknown. Whenever a node is visited by an agent, its
neighborhood and adjacent edges are revealed. The agents share a global view of
the explored parts of the graph. The cost of the exploration has to be
minimized, where cost either describes the time needed for the entire
exploration (time model), or the length of the longest path traversed by any
agent (energy model). We investigate graph exploration on cycles and tadpole
graphs for 2-4 agents, providing optimal results on the competitive ratio in
the energy model (1-competitive with two agents on cycles and three agents on
tadpole graphs), and for tadpole graphs in the time model (1.5-competitive with
four agents). We also show competitive upper bounds of 2 for the exploration of
tadpole graphs with three agents, and 2.5 for the exploration of tadpole graphs
with two agents in the time model.
