Fractals2019: Combinatorial Optimisation with Dynamic Constraint Annealing

3Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Fractals2019 started as a new experimental entry in the RoboCup Soccer 2D Simulation League, based on Gliders2d code base, and advanced to become a RoboCup-2019 champion. We employ combinatorial optimisation methods, within the framework of Guided Self-Organisation, with the search guided by local constraints. We present examples of several tactical tasks based on the Gliders2d code (version v2), including the search for an optimal assignment of heterogeneous player types, as well as blocking behaviours, offside trap, and attacking formations. We propose a new method, Dynamic Constraint Annealing, for solving dynamic constraint satisfaction problems, and apply it to optimise thermodynamic potential of collective behaviours, under dynamically induced constraints.

Cite

CITATION STYLE

APA

Prokopenko, M., & Wang, P. (2019). Fractals2019: Combinatorial Optimisation with Dynamic Constraint Annealing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11531 LNAI, pp. 616–630). Springer. https://doi.org/10.1007/978-3-030-35699-6_50

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free