Energy Structure of Optimal Positional Strategies in Mean Payoff Games
Carlo Comin

TL;DR
This paper explores the structure of optimal positional strategies in mean payoff games, revealing a unique decomposition into extremal energy measures, and provides an efficient recursive enumeration method for these structures.
Contribution
It introduces the concept of an energy-lattice of extremal-SEPMs and a recursive procedure to enumerate all elements, advancing the understanding of strategy structures in MPGs.
Findings
The energy-lattice of OPSs is characterized by least-SEPMs of basic subgames.
A pseudo-polynomial recursive enumeration procedure is proposed.
The complexity of enumeration is polynomial in game size and energy measures.
Abstract
This note studies structural aspects concerning Optimal Positional Strategies (OPSs) in Mean Payoff Games (MPGs), it is a contribution to understanding the relationship between OPSs in MPGs and Small Energy-Progress Measures (SEPMs) in reweighted Energy Games (EGs). Firstly, it is observed that the space of all OPSs, , admits a unique complete decomposition in terms of so-called extremal-SEPM{s} in reweighted EG{s}; this points out what we called the "Energy-Lattice of ". Secondly, it is offered a pseudo-polynomial total-time recursive procedure for enumerating (w/o repetitions) all the elements of , and for computing the corresponding partitioning of . It is observed that the corresponding recursion tree defines an additional lattice…
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Taxonomy
TopicsFormal Methods in Verification · Optimization and Search Problems · Constraint Satisfaction and Optimization
