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Bernhard Nebel.
The Computational Complexity of MultiAgent Pathfinding on Directed Graphs.
Artificial Intelligence. 2024.
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(Preprint; PDF)
(Online; DOI)
While the nonoptimizing variant of multiagent pathfinding on undirected graphs is known to be a polynomialtime problem since almost forty years, a similar result has not been established for directed graphs. In this paper, it will be shown that this problem is NPcomplete. For strongly connected directed graphs, however, the problem is polynomial. And both of these results hold even if one allows for synchronous rotations on fully occupied cycles. Interestingly, the results apply also to the socalled motion planning feasibility problem on directed graphs.

Moritz Graf, Thorsten Engesser und Bernhard Nebel.
A Symbolic Sequential Equilibria Solver for Game Theory Explorer (Demo Track).
In
Proceedings of the 23rd Int. Joint Conf. on Autonomous Agents and Multiagent Systems
(AAMAS 2024).
2024.
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We present the first implemented symbolic solver for sequential equilibria in general finite imperfect information games.

Moritz Graf, Thorsten Engesser und Bernhard Nebel.
Symbolic Computation of Sequential Equilibria.
In
Proceedings of the 23rd Int. Joint Conf. on Autonomous Agents and Multiagent Systems
(AAMAS 2024).
2024.
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The sequential equilibrium is a standard solution concept for extensiveform games with imperfect information that includes an explicit representation of the players' beliefs. An assessment consisting of a strategy and a belief is a sequential equilibrium if it satisfies the properties of sequential rationality and consistency.
Our main result is that both properties together can be written as a finite set of polynomial equations and inequalities. The solutions to this system are exactly the sequential equilibria of the game. We construct this system explicitly and describe an implementation that solves it using cylindrical algebraic decomposition. To write consistency as a finite system of equations, we need to compute the extreme directions of a set of polyhedral cones. We propose a modified version of the double description method, optimized for this specific purpose. To the best of our knowledge, our implementation is the first to symbolically solve general finite imperfect information games for sequential equilibria.

Stefano Ardizzoni, Irene Saccani, Luca Consolini, Marco Locatelli und Bernhard Nebel.
An Algorithm with Improved Complexity for Pebble Motion/MultiAgent Path Finding on Trees.
Journal of Artificial Intelligence Research 79. 2024.
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(Online; DOI)
The pebble motion on trees (PMT) problem consists in finding a feasible sequence of moves that repositions a set of pebbles to assigned target vertices. This problem has been widely studied because, in many cases, the more general MultiAgent path finding (MAPF) problem on graphs can be reduced to PMT. We propose a simple and easy to implement procedure, which finds solutions of length O(Pnc + n2), where n is the number of nodes, P is the set of pebbles, and c the maximum length of corridors in the tree. This complexity result is more detailed than the current best known result O(n3), which is equal to our result in the worst case, but does not capture the dependency on c and P.