Polynomial-Time Algorithms for Energy Games with Special Weight Structures

TL;DR

This paper introduces polynomial-time algorithms for certain subclasses of energy games based on weight structures, solving longstanding open problems and demonstrating practical efficiency in specific cases.

Contribution

It presents the first polynomial-time algorithms for energy games with large penalty weights and clustered weights, expanding the classes of graphs solvable efficiently.

Findings

Polynomial-time algorithm for graphs with large penalty.

Efficient solution when weights are clustered around few values.

Complexity remains high for graphs with bounded clique-width or strong ergodicity.

Abstract

Energy games belong to a class of turn-based two-player infinite-duration games}played on a weighted directed graph. It is one of the rare and intriguing combinatorial problems that lie in ${\sf NP} \cap {\sf co\mbox{-}NP}$, but are not known to be in ${\sf P}$. The existence of polynomial-time algorithms has been a major open problem for decades and apart from pseudopolynomial algorithms there is no algorithm that solves any non-trivial subclass in polynomial time. In this paper, we give several results based on the weight structures of the graph. First, we identify a notion of penalty and present a polynomial-time algorithm when the penalty is large. Our algorithm is the first polynomial-time algorithm on a large class of weighted graphs. It includes several worst-case instances on which previous algorithms, such as value iteration and random facet algorithms, require at least sub-exponential time. Our main technique is developing the first non-trivial approximation algorithm and showing how to convert it to an exact algorithm. Moreover, we show that in a practical case in verification where weights are clustered around a constant number of values, the energy game problem can be solved in polynomial time. We also show that the problem is still as hard as in general when the clique-width is bounded or the graph is strongly ergodic, suggesting that restricting the graph structure does not necessarily help.