Limit Your Consumption! Finding Bounds in Average-energy Games

TL;DR

This paper investigates methods to determine bounds on average energy consumption in infinite two-player energy games, providing complexity results and exploring tradeoffs between memory and energy bounds.

Contribution

It introduces complexity classifications for bounding average energy in classical and recharge energy games, and analyzes strategy memory versus energy bounds tradeoffs.

Findings

Determining bounds in classical energy games is doubly-exponential time.

Bounding average energy in recharge games is exponential time complete.

Existence of a suitable recharge capacity can be decided in polynomial time.

Abstract

Energy games are infinite two-player games played in weighted arenas with quantitative objectives that restrict the consumption of a resource modeled by the weights, e.g., a battery that is charged and drained. Typically, upper and/or lower bounds on the battery capacity are part of the problem description. Here, we consider the problem of determining upper bounds on the average accumulated energy or on the capacity while satisfying a given lower bound, i.e., we do not determine whether a given bound is sufficient to meet the specification, but if there exists a sufficient bound to meet it. In the classical setting with positive and negative weights, we show that the problem of determining the existence of a sufficient bound on the long-run average accumulated energy can be solved in doubly-exponential time. Then, we consider recharge games: here, all weights are negative, but there are recharge edges that recharge the energy to some fixed capacity. We show that bounding the long-run average energy in such games is complete for exponential time. Then, we consider the existential version of the problem, which turns out to be solvable in polynomial time: here, we ask whether there is a recharge capacity that allows the system player to win the game. We conclude by studying tradeoffs between the memory needed to implement strategies and the bounds they realize. We give an example showing that memory can be traded for bounds and vice versa. Also, we show that increasing the capacity allows to lower the average accumulated energy.