The Large Synoptic Survey Telescope will complete its survey in 2022 and produce terabytes of imaging data each night. To work with this massive onset of data, automated algorithms to classify astronomical light curves are crucial. Here, we present a method for automated classification of photometric light curves for a range of astronomical objects. Our approach is based on the gradient boosting of decision trees, feature extraction and selection, and augmentation. The solution was developed in the context of The Photometric LSST Astronomical Time Series Classification Challenge (PLAsTiCC) and achieved one of the top results in the challenge.

Fractals2019 started as a new experimental entry in the RoboCup Soccer 2D Simulation League, based on Gliders2d code base, and advanced to a team winning RoboCup-2019 championship. Our approach is centred on combinatorial optimisation methods, within the framework of Guided Self-Organisation (GSO), with the search guided by local constraints. We present examples of several tactical tasks based on the fully released 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. 1 Introduction The RoboCup Soccer 2D Simulation League provides a rich dynamic environment, facilitated by the RoboCup Soccer Simulator (RCSS), aimed to test advances in decentralised collective behaviours of autonomous agents. The challenges include concurrent adversarial actions, computational nondetermin-ism, noise and latency in asynchronous perception and actuation, and limited processing time [1-9]. Over the years the progress of the League has been supported by several important base code releases, covering both low-level skills and standardised world models of simulated agents [10-13]. The release in 2010 of the base code of HELIOS team, agent2d-3.0.0, later upgraded to agent2d-3.1.1,

The selection of an appropriate competition format is critical for both the success and credibility of any competition, both real and simulated. In this paper, the automated parallelism offered by the RoboCupSoccer 2D simulation league is leveraged to conduct a 28,000 game round-robin between the top 8 teams from RoboCup 2012 and 2013. A proposed new competition format is found to reduce variation from the resultant statistically significant team performance rankings by 75% and 67%, when compared to the actual competition results from RoboCup 2012 and 2013 respectively. These results are statistically validated by generating 10,000 random tournaments for each of the three considered formats and comparing the respective distributions of ranking discrepancy.

The RoboCup 2D Simulation League incorporates several challenging features, setting a benchmark for Artificial Intelligence (AI). In this paper we describe some of the ideas and tools around the development of our team, Gliders2012. In our description, we focus on the evaluation function as one of our central mechanisms for action selection. We also point to a new framework for watching log files in a web browser that we release for use and further development by the RoboCup community. Finally, we also summarize results of the group and final matches we played during RoboCup 2012, with Gliders2012 finishing 4th out of 19 teams.