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Graph exploration by a single agent

One agent starts at a node of an unknown anonymous graph and must visit every node; how much memory does it need, which pebbles or knowledge make it possible, and how fast can it be?

Problem statement and measuresexpand

A single deterministic agent is placed at a node \(s\) of a connected graph \(G\) with \(n\) nodes, \(m\) edges and maximum degree \(\Delta\). Nodes are anonymous (they carry no names the agent can read), and the edges at each node are numbered locally; these numbers are the node's ports. The agent sees the degree of its node and the port by which it entered. It must visit every node of \(G\). Three termination requirements are standard:

  • perpetual exploration: every node is eventually visited; the agent never has to stop;
  • exploration with stop: every node is visited and the agent then stops, anywhere;
  • exploration with return: every node is visited and the agent stops at \(s\).

Return implies stop, and stop implies perpetual exploration. Memory is the number of bits of the agent's state; when the agent carries pebbles (objects it can drop on a node and pick up again) their number is reported with the memory. Time is the number of moves (edge traversals) until exploration is complete; for periodic exploration it is the period. Unless a variant says otherwise the agent knows nothing about \(G\), not even \(n\).

Exploration is the oldest problem of the mobile-agent literature: it started as maze search by finite automata, and the question of how little memory suffices runs from Budach's impossibility (1978) to Reingold's log-space algorithm (2005). Several agents exploring together form the sibling problem, collaborative exploration.

Measures: Time, edge traversals until every node is visited (for periodic exploration: the period); Memory, bits of agent memory; pebbles, if any, are counted separately.

Node labels chosen by the designer

verified
Time: unknownMemory: tight

With three-valued labels on the nodes, an agent with fewer than 25 states explores every graph and stops after at most \(20m\) edge traversals.

Assumed (added on the last edge are outlined)

+Graph dynamicsstatic graph+Edge directionundirected+Preprocessingshort node labels chosen by the designer+Termination requirementexplore, then stop anywhere

Not assumed

Node identifiersanonymous nodesKnowledgenothing known about the graphRandomnessdeterministicMarkersno markersTopologyarbitrary connected graph
Formal definitions of this setting
Graph dynamics: static graph
\(G_t=G\) for all \(t\): the edge set never changes.
Edge direction: undirected
\(G=(V,E)\) with \(E\subseteq\binom V2\); every edge can be traversed in both directions.
Node identifiers: anonymous nodes
Nodes have no identifiers; an agent at \(v\) sees only \(\deg(v)\) and the port numbers \(1,\dots,\deg(v)\), which are assigned locally and independently at each endpoint of an edge.
Knowledge: nothing known
The agent knows nothing about \(G\): not \(n\), \(m\), \(\Delta\) or \(D\).
Randomness: deterministic
The next state and move of an agent are a function of its current state and what it observes.
Markers: no markers
The agent cannot mark nodes.
Preprocessing: designer labels
Before the agent starts, the designer may write a label of \(b\) bits (a constant) at every node, which the agent reads on arrival.
Termination requirement: with stop
The agent visits every node and then halts, at any node. Also called terminating exploration.
Topology: any topology
\(G\) is any connected graph in the class allowed by the other axes.

What is known

Time · edge traversals until every node is visited (for periodic exploration: the period)
unknown
Only the trivial \(\Omega(n)\) is known against \(O(m)\).
lower boundnone known
introductory—
current best
\(O(m)\)
labels of 2 bits (3 values), computed in linear time
Memory · bits of agent memory; pebbles, if any, are counted separately
tight
Constant memory.
lower boundnone known
introductory—
current best
\(O(1)\)
labels of 2 bits (3 values), computed in linear time

Results, in order of publication

Cohen et al. 2008 current best
Time \(O(m)\)Memory \(O(1)\)
labels of 2 bits (3 values), computed in linear time

Introductory and current best (Theorem 2.1): fewer than 25 states, at most \(20m\) edge traversals, stops at a node chosen by the designer. Labelling while exploring gives \(O(Dm)\).

Time \(O(\Delta^{10}m)\)Memory \(O(\log\Delta)\)
labels of 1 bit

Theorem 3.1.

Open questions

None recorded for this variant.

Notes

The agent is a Mealy automaton: its output port depends on the input port. Agents with a single state cannot explore all graphs with such labels (Theorems 4.2 and 4.5 of Cohen et al. 2008). Recent work changes the model: zero-memory agents that do not see the entry port but may colour nodes (SIROCCO 2023, OPODIS 2025); these are not catalogued yet. Checked against the full text.

What carries over from neighbouring settings

Read off the order of assumptions, not checked case by case: results may carry extra assumptions (shown on their pages), and asynchronous time is measured in epochs.

Algorithms from weaker settings work here

Lower bounds from stronger settings hold here

No catalogued stronger setting.

Know a better result for this setting, or found a mistake? Suggest a result · Report an error. Accepted contributions are acknowledged.