Ms Pac-Man versus Ghost Team CEC 2011 competition

Games provide an ideal test bed for computational intelligence and significant progress has been made in recent years, most notably in games such as Go, where the level of play is now competitive with expert human play on smaller boards. Recently, a significantly more complex class of games has received increasing attention: real-time video games. These games pose many new challenges, including strict time constraints, simultaneous moves and open-endedness. Unlike in traditional board games, computational play is generally unable to compete with human players. One driving force in improving the overall performance of artificial intelligence players are game competitions where practitioners may evaluate and compare their methods against those submitted by others and possibly human players as well. In this paper we introduce a new competition based on the popular arcade video game Ms Pac-Man: Ms Pac-Man versus Ghost Team. The competition, to be held at the Congress on Evolutionary Computation 2011 for the first time, allows participants to develop controllers for either the Ms Pac-Man agent or for the Ghost Team and unlike previous Ms Pac-Man competitions that relied on screen capture, the players now interface directly with the game engine. In this paper we introduce the competition, including a review of previous work as well as a discussion of several aspects regarding the setting up of the game competition itself. © 2011 IEEE

Demonstration of PI2: Interactive Visualization Interface Generation for SQL Analysis in Notebook

We demonstrate PI2, the first notebook extension that can automatically generate interactive visualization interfaces during SQL-based analyses.Comment: arXiv admin note: text overlap with arXiv:2107.0820

Fast Approximate Max-n Monte Carlo Tree Search for Ms Pac-Man

We present an application of Monte Carlo tree search (MCTS) for the game of Ms Pac-Man. Contrary to most applications of MCTS to date, Ms Pac-Man requires almost real-time decision making and does not have a natural end state. We approached the problem by performing Monte Carlo tree searches on a five player maxn tree representation of the game with limited tree search depth. We performed a number of experiments using both the MCTS game agents (for pacman and ghosts) and agents used in previous work (for ghosts). Performance-wise, our approach gets excellent scores, outperforming previous non-MCTS opponent approaches to the game by up to two orders of magnitude. © 2011 IEEE

CheckMATE 2: From the model to the limit

We present the latest developments to the CheckMATE program that allows models of new physics to be easily tested against the recent LHC data. To achieve this goal, the core of CheckMATE now contains over 60 LHC analyses of which 12 are from the 13 TeV run. The main new feature is that CheckMATE 2 now integrates the Monte Carlo event generation via Madgraph and Pythia 8. This allows users to go directly from a SLHA file or UFO model to the result of whether a model is allowed or not. In addition, the integration of the event generation leads to a significant increase in the speed of the program. Many other improvements have also been made, including the possibility to now combine signal regions to give a total likelihood for a model.Comment: 53 pages, 6 figures; references updated, instructions slightly change

Generating renderers

Most production renderers developed for the film industry are huge pieces of software that are able to render extremely complex scenes. Unfortunately, they are implemented using the currently available programming models that are not well suited to modern computing hardware like CPUs with vector units or GPUs. Thus, they have to deal with the added complexity of expressing parallelism and using hardware features in those models. Since compilers cannot alone optimize and generate efficient programs for any type of hardware, because of the large optimization spaces and the complexity of the underlying compiler problems, programmers have to rely on compiler-specific hardware intrinsics or write non-portable code. The consequence of these limitations is that programmers resort to writing the same code twice when they need to port their algorithm on a different architecture, and that the code itself becomes difficult to maintain, as algorithmic details are buried under hardware details. Thankfully, there are solutions to this problem, taking the form of Domain-Specific Lan- guages. As their name suggests, these languages are tailored for one domain, and compilers can therefore use domain-specific knowledge to optimize algorithms and choose the best execution policy for a given target hardware. In this thesis, we opt for another way of encoding domain- specific knowledge: We implement a generic, high-level, and declarative rendering and traversal library in a functional language, and later refine it for a target machine by providing partial evaluation annotations. The partial evaluator then specializes the entire renderer according to the available knowledge of the scene: Shaders are specialized when their inputs are known, and in general, all redundant computations are eliminated. Our results show that the generated renderers are faster and more portable than renderers written with state-of-the-art competing libraries, and that in comparison, our rendering library requires less implementation effort.Die meisten in der Filmindustrie zum Einsatz kommenden Renderer sind riesige Softwaresysteme, die in der Lage sind, extrem aufwendige Szenen zu rendern. Leider sind diese mit den aktuell verfügbaren Programmiermodellen implementiert, welche nicht gut geeignet sind für moderne Rechenhardware wie CPUs mit Vektoreinheiten oder GPUs. Deshalb müssen Entwickler sich mit der zusätzlichen Komplexität auseinandersetzen, Parallelismus und Hardwarefunktionen in diesen Programmiermodellen auszudrücken. Da Compiler nicht selbständig optimieren und effiziente Programme für jeglichen Typ Hardware generieren können, wegen des großen Optimierungsraumes und der Komplexität des unterliegenden Kompilierungsproblems, müssen Programmierer auf Compiler-spezifische Hardware-“Intrinsics” zurückgreifen, oder nicht portierbaren Code schreiben. Die Konsequenzen dieser Limitierungen sind, dass Programmierer darauf zurückgreifen den gleichen Code zweimal zu schreiben, wenn sie ihre Algorithmen für eine andere Architektur portieren müssen, und dass der Code selbst schwer zu warten wird, da algorithmische Details unter Hardwaredetails verloren gehen. Glücklicherweise gibt es Lösungen für dieses Problem, in der Form von DSLs. Diese Sprachen sind maßgeschneidert für eine Domäne und Compiler können deshalb Domänenspezifisches Wissen nutzen, um Algorithmen zu optimieren und die beste Ausführungsstrategie für eine gegebene Zielhardware zu wählen. In dieser Dissertation wählen wir einen anderen Weg, Domänenspezifisches Wissen zu enkodieren: Wir implementieren eine generische, high-level und deklarative Rendering- und Traversierungsbibliothek in einer funktionalen Programmiersprache, und verfeinern sie später für eine Zielmaschine durch Bereitstellung von Annotationen für die partielle Auswertung. Der “Partial Evaluator” spezialisiert dann den kompletten Renderer, basierend auf dem verfügbaren Wissen über die Szene: Shader werden spezialisiert, wenn ihre Eingaben bekannt sind, und generell werden alle redundanten Berechnungen eliminiert. Unsere Ergebnisse zeigen, dass die generierten Renderer schneller und portierbarer sind, als Renderer geschrieben mit den aktuellen Techniken konkurrierender Bibliotheken und dass, im Vergleich, unsere Rendering Bibliothek weniger Implementierungsaufwand erfordert.This work was supported by the Federal Ministry of Education and Research (BMBF) as part of the Metacca and ProThOS projects as well as by the Intel Visual Computing Institute (IVCI) and Cluster of Excellence on Multimodal Computing and Interaction (MMCI) at Saarland University. Parts of it were also co-funded by the European Union(EU), as part of the Dreamspace project