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Treasure hunt

One agent must find a static treasure at an unknown node; the cost should depend on how far the treasure is, not on the size of the graph.

Problem statement and measuresexpand

A single deterministic agent starts at a node \(s\) of an unknown connected graph whose edges carry ports (at each node, local numbers of the edges at that node); a treasure sits at an unknown node \(v^*\) at distance \(d\) from \(s\). The agent must reach \(v^*\) (it recognises the treasure when it arrives). Cost is the number of moves (edge traversals) until the treasure is found, measured against \(d\), against \(e(d)\) (the number of edges with an endpoint at distance less than \(d\) from \(s\)) or against a path weight defined per paper. Help counts any external help the agent receives: bits of advice from an oracle that knows the instance, or pebbles (objects left on nodes) placed by it. Unless a variant says otherwise the agent knows nothing about the graph, \(d\) or \(v^*\).

Measures: Cost, edge traversals until the treasure is reached; Help, bits of advice, or pebbles placed in advance by an oracle.

tight near-optimal polynomial gap unknown impossible· rows follow the assumption tree; each cell: best upper bound vs lower bound, and what forces the lower bound
Setting
Cost
Help
Anonymous graphs with possibly infinite degrees + static graph, + undirected
0 open · 1 results
tight \(O(w(s,v^*))\) vs \(\Omega(w(s,v^*))\) port addressing
tight — vs —
Anonymous finite graphs + finite graph
2 open · 2 results
unknown \(O(n^{\theta(1+1/a)})\) vs —
unknown — vs —
Treasure hunt with advice + advice
0 open · 1 results
tight \(C\) vs —
near-optimal \(O(d\log(d\cdot m/C)+\log\log m)\) vs \(\Omega(d\log(m/C))\) information
Treasure hunt guided by pebbles + oracle pebbles
0 open · 1 results
near-optimal \(O(d\log\Delta+\log^3\Delta)\) vs \(\Omega(d\log\Delta)\) port addressing
unknown \(O(d\log\Delta)\ \text{pebbles}\) vs —
Labelled nodes, locally finite graphs + locally finite, + labelled nodes
1 open · 1 results
near-optimal \(O(e(d)\log d)\) vs \(\Omega(e(d))\) distance
tight — vs —

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