SSCAIT 2015/16
The 2015/16 installment of SSCAIT sported 46 participants. The tournament was divided into two divisions:
- Student division: Round Robin tournament of 1035 games, where everybody played one game against everybody else. Only the students were eligible for prizes.
- Mixed division: Elimination bracket of 16 best bots (including non-students and teams).
Student division results:
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Mixed division videos:All the mixed elimination games can be watched in this YouTube playlist |
Mixed division 2015/16 Elimination Bracket results:
Overall scores (both divisions) after round-robin 2015:
| Name | Race | Wins | Losses | Score | Avg. Score | Achievements | Division | Description |
 Marian Devecka | Zerg | 43 | 2 | 43 | 0.96 | 21:                      | Mixed (non-competitive) | Savage zerg bot. Shows no mercy. |
 Igor Dimitrijevic | Terran | 42 | 3 | 42 | 0.93 | 11: | Mixed (non-competitive) | Stone 1.0 http://bwem.sourceforge.net/Stone.html |
 tscmoop | Protoss | 41 | 4 | 41 | 0.91 | 12: | Mixed (non-competitive) | Protoss yey :D |
 Chris Coxe | Zerg | 38 | 7 | 38 | 0.84 | 12: | Mixed (non-competitive) | https://github.com/chriscoxe/ZZZKBot: A simple throw-away proof-of-concept cheesy kamikaze 4-pool bot implemented in a short amount of time to reach low-hanging fruit. Effective against many bots that do not have a solid opening economy/defence. |
 Martin Rooijackers | Terran | 37 | 8 | 37 | 0.82 | 21: | Student: University Maastricht | LetaBot: A Terran bot with wall-in implementation. Uses many different strategies. Based on Nova and UAlberta bot. LetaBot uses Liquipedia Build orders, text mined by Dennis Soemers. |
 Andrew Smith | Protoss | 35 | 10 | 35 | 0.78 | 21: | Mixed (non-competitive) | Version 2.1 of Skynet |
Sijia Xu | Zerg | 35 | 10 | 35 | 0.78 | 12: | Mixed (non-competitive) | https://github.com/sijiaxu/Overkill |
Carsten Nielsen | Protoss | 35 | 10 | 35 | 0.78 | 20: | Student: Technical University of Denmark | Simple WIP zealot rush-bot. |
 ICELab | Terran | 35 | 10 | 35 | 0.78 | 23:   | Mixed (non-competitive) | ICEbot 2.1 from Intelligent Computer Entertainment Lab., Ritsumeikan University. Potential flows, finite state machine, enemy strategy prediction which triggers adaptive strategy rules and a lot of other heuristic things are applied in this bot. |
 Dave Churchill | Random | 34 | 11 | 34 | 0.76 | 23: | Student: University of Alberta | https://github.com/davechurchill/ualbertabot |
 Tomas Vajda | Protoss | 33 | 12 | 33 | 0.73 | 24:  | Mixed (non-competitive) | XIMP bot. Carrier push. |
 Odin2014 | Protoss | 29 | 16 | 29 | 0.64 | 19: | Mixed (non-competitive) | Odin is a bot developed during a Bachelor thesis project. It is based on UAlbertaBot and uses Bayesian networks to predict the opponent. More information at http://plankter.se/projects/odin/ . |
Soeren Klett | Terran | 29 | 16 | 29 | 0.64 | 24: | Student: University of Bielefeld | W.O.P.R - Bot - Monitoring and replanning |
 Marcin Bartnicki | Zerg | 29 | 16 | 29 | 0.64 | 18: | Mixed (non-competitive) | Simple 6pool bot |
 Aurelien Lermant | Zerg | 29 | 16 | 29 | 0.64 | 16: | Student: Epita, Paris | GarmBot is a Macro-heavy bot, expanding rapidly to try and overwhelm the enemy with an unstopable stream of zerg units. For now, this bot uses zerglings and hydralisks for attack, and queens to harass. Late game, guardians and devourers join the fight. |
Florian Richoux | Protoss | 26 | 19 | 26 | 0.58 | 23: | Mixed (non-competitive) | AIUR v2.2. Please visit aiur-group.github.io/AIUR/ for further information. |
 Simon Prins | Terran | 25 | 20 | 25 | 0.56 | 19: | Mixed (non-competitive) | Bot by the name of Tyr. Battlecruisers... mech... bio? What is going on!? |
 La Nuee | Zerg | 24 | 21 | 24 | 0.53 | 6: | Mixed (non-competitive) | |
 A Jarocki | Zerg | 24 | 21 | 24 | 0.53 | 11: | Student | "HelloWorld" type of zerg bot |
Marek Suppa | Zerg | 24 | 21 | 24 | 0.53 | 20: | Student: Comenius University, Bratislava | It's a simple, stupid 5 pool implemented in a simple, stupid language that shall remain anonymous. |
krasi0 | Terran | 24 | 21 | 24 | 0.53 | 23: | Mixed (non-competitive) | Involves some super secret AI technologies :P |
Tomas Cere | Protoss | 23 | 22 | 23 | 0.51 | 21: | Mixed (non-competitive) | Simple Protoss bot. |
Jakub Trancik | Protoss | 23 | 22 | 23 | 0.51 | 21: | Student: Comenius University, Bratislava | Simple toss bot utilizing potential fields, with building placement trained by a genetic algorithm. |
 Gaoyuan Chen | Protoss | 21 | 24 | 21 | 0.47 | 17: | Student: University of Southern California | Reaver with Shuttle |
Roman Danielis | Protoss | 20 | 25 | 20 | 0.44 | 20: | Student: Comenius University, Bratislava | Heuristic bot with adaptive army composition. |
Igor Lacik | Terran | 20 | 25 | 20 | 0.44 | 21: | Student: Comenius University, Bratislava | The bot consists of state machine managers which frequently use simple heuristics to perform game tasks. It uses Terran bio strategy with simple micro managing, scouting, somewhat easy yet satisfying heuristics for expansions selection. |
Daniel Blackburn | Zerg | 20 | 25 | 20 | 0.44 | 21: | Student: University of Washington | It's a simple 4pool bot. If it beats your bot even once...I have bad news for you. |
 Chris Ayers | Protoss | 19 | 26 | 19 | 0.42 | 10: | Mixed (non-competitive) | this is a tweaked bot of Adam Montgomerie moosebot all credit goes to him and ualberta still learning and testing with this. Still not undersanding! Any help is welcomed. |
Matej Istenik | Terran | 18 | 27 | 18 | 0.4 | 23: | Student: University of Zilina | Simple Terran bot based on agents, state machines and lots of ifs. |
NUS Bot | Protoss | 17 | 28 | 17 | 0.38 | 13: | Student: National University of Singapore | A team of five MTech Knowledge Engineering students, GU Zhan, Francisco Liwa, He Tao, Liu Jie, Jinson Xu, developed an intelligent software robot: NUS-Bot by using advanced techniques taught in the MTech program.This NUS-Bot represents Singapore for the |
Oleg Ostroumov | Terran | 17 | 28 | 17 | 0.38 | 19: | Mixed (non-competitive) | 1 base "Sparks" Terran play |
Marek Kadek | Terran | 16 | 29 | 16 | 0.36 | 21: | Student: Comenius University, Bratislava | Terran bot using priorities generated based on various input with army composition based on enemy's. |
Martin Dekar | Terran | 16 | 29 | 16 | 0.36 | 18: | Student: Charles University, Prague | Simple Marines and Medics Terran bot. Features:Scouting,StimPacks,focus fire,smart groups,infantry upgrades,groups SCV's against rushes,Comsat.At the moment the bot doesn't build expansions or advanced units. |
 Radim Bobek | Terran | 15 | 30 | 15 | 0.33 | 6: | Student: Czech Technical University in Prague | Very basic bot 2.0 with rush tactic. It was made on 3day workshop in Prague. |
 Tomasz Michalski | Zerg | 13 | 32 | 13 | 0.29 | 0: | Student: ZS Polaniec | Very simple zerg bot |
 Serega | Zerg | 13 | 32 | 13 | 0.29 | 15: | Mixed (non-competitive) | 5 pool (everyone has to start somewhere) |
EradicatumXVR | Terran | 12 | 33 | 12 | 0.27 | 18: | Mixed (non-competitive) | Need help with your life? Tired of Zealots in your garden? Eradicate problems from your life with brand new EradicatumXVR and its long-range tanks! |
Vladimir Jurenka | Protoss | 12 | 33 | 12 | 0.27 | 18: | Student: Comenius University, Bratislava | Old bot for SSCAI Tournament 2012 |
OpprimoBot | Random | 12 | 33 | 12 | 0.27 | 9: | Mixed (non-competitive) | OpprimoBot is the first and currently only bot in SSCAIT to play with random race! It is constructed around a modular multi-agent system to make it flexible enough to handle all three races. |
Adrian Sternmuller | Zerg | 11 | 34 | 11 | 0.24 | 15: | Student: Comenius University, Bratislava | Simple Hydra bot. |
 UPStarcraftAI | Terran | 10 | 35 | 10 | 0.22 | 0: | Mixed (non-competitive) | This bot uses a Terran bio ball strategy with marines and medics to try and overwhelm the opponent. Created by 4 students at the University of Portland, Casey Sigelmann, Kenny Trowbridge, Alex Bowns, and Max Robinson. |
Bjorn P Mattsson | Zerg | 10 | 35 | 10 | 0.22 | 13: | Student: Chalmers University of Technology, Gothenburg, Sweden | Loki_v0.13. At the moment expanding and massing zerglings. Read more at https://bitbucket.org/Plankton555/loki/wiki/Home |
Pablo Garcia Sanchez | Zerg | 8 | 37 | 8 | 0.18 | 0: | Mixed (non-competitive) | Bot created with StarcraftGP, a Genetic Programming algorithm presented in paper "Towards Automatic StarCraft Strategy Generation Using Genetic Programming" (CIG 2015). It is based in OpprimoBot source. |
Martin Strapko | Protoss | 7 | 38 | 7 | 0.16 | 11: | Student: Comenius University, Bratislava | All in pushing protoss with some random on purpose dragoons AlphaBeta pruning movement that could be called "micro". Some christmas suprises might await us all! :D |
Jan Pajan | Terran | 6 | 39 | 6 | 0.13 | 6: | Student: Comenius University, Bratislava | Terran bot from SSCAI 2012. |
 Karin Valisova | Terran | 5 | 40 | 5 | 0.11 | 4: | Student: Comenius University, Bratislava | This gentle bot with humble functionality is build on the idea of optimizing the ratio of the military units by hillclimb algorithm. |