Shallow decision-making analysis in General Video Game Playing

The General Video Game AI competitions have been the testing ground for several techniques for game playing, such as evolutionary computation techniques, tree search algorithms, hyper heuristic based or knowledge based algorithms. So far the metrics used to evaluate the performance of agents have been win ratio, game score and length of games. In this paper we provide a wider set of metrics and a comparison method for evaluating and comparing agents. The metrics and the comparison method give shallow introspection into the agent's decision making process and they can be applied to any agent regardless of its algorithmic nature. In this work, the metrics and the comparison method are used to measure the impact of the terms that compose a tree policy of an MCTS based agent, comparing with several baseline agents. The results clearly show how promising such general approach is and how it can be useful to understand the behaviour of an AI agent, in particular, how the comparison with baseline agents can help understanding the shape of the agent decision landscape. The presented metrics and comparison method represent a step toward to more descriptive ways of logging and analysing agent's behaviours

Laser Dissimilar Joining of Al7075T6 with Glass-Fiber-Reinforced Polyamide Composite

Dissimilar joining between metal and composite sheets is usually carried out by mechanical or adhesive joining. Laser dissimilar joining between metal and composite sheets could be an alternative to these methods, as it is a cost-effective and versatile joining technique. Previously, textured metallic and composite parts have been held together and heated with a laser beam while pressure is applied to allow the melted polymer to flow into the cavities of the metal part. The main issue of this process relates to reaching the same joint strength repetitively with appropriate process parameters. In this work, both initial texturing and laser joining parameters are studied for Al 7075-T6 and glass-fiber-reinforced PA6 composite. A groove-based geometry was studied in terms of depth-to-width aspect ratio to find an optimal surface using a nanosecond fiber laser for texturing. Laser joining parameters were also studied with different combinations of surface temperature, heating strategy, pressure, and laser feed rate. The results are relatively good for grooves with aspect ratios from 0.94 to 4.15, with the widths of the grooves being the most critical factor. In terms of joining parameters, surface reference temperature was found to be the most influential parameter. Underheating does not allow correct material flow in textured cavities, while overheating also causes high dispersion in the resulting shear strength. When optimal parameters are applied using correct textures, shear strength values over 26 kN are reached, with a contact area of 35 × 45 mm2.This research was funded by the Basque Government grant number KK-2017/00088

Ensemble decision systems for general video game playing

Ensemble Decision Systems offer a unique form of decision making that allows a collection of algorithms to reason together about a problem. Each individual algorithm has its own inherent strengths and weaknesses, and often it is difficult to overcome the weaknesses while retaining the strengths. Instead of altering the properties of the algorithm, the Ensemble Decision System augments the performance with other algorithms that have complementing strengths. This work outlines different options for building an Ensemble Decision System as well as providing analysis on its performance compared to the individual components of the system with interesting results, showing an increase in the generality of the algorithms without significantly impeding performance.Comment: 8 Pages, Accepted at COG201

Predictive Models and Monte Carlo Tree Search: A Pipeline for Believable Agents

Developing and assessing believable agents remains a sought out challenge. Recently, research has approached this problem by treating and assessing believability as a time-continuous phenomenon, learning from collected data to predict believability of games and game states. Our study will build on this work: by integrating this believability model with a game agent to affect its behaviour. In this short paper, we first describe our methodology and then the results obtained from our user study, which suggests that this methodology can help creating more believable agents, opening the possibility of integrating this type of models into game development. We also discuss the limitations of this approach, possible variants to tackle these, and ideas for future work to extend this preliminary work

Sistemas de predistorsión-linealización para enlaces ópticos

Ante el aumento de la demanda de conectividad de una sociedad cada vez más basada en las comunicaciones, la nueva generación de redes de transmisión apuesta claramente por la preeminencia de las tecnologías ópticas. No solo las redes troncales sino también en el acceso al hogar y en la alimentación de antenas de telefonía móvil y satélite. En este contexto en este TFC se diseñarán, se construirán y se medirán las prestaciones de circuitos de radiofrecuencia de predistorsión en el emisor y de ecualización en el receptor para la optimización de enlaces con amplificación óptica y detección directa en el receptor

Balancing Wargames through Predicting Unit Point Costs

In tactical wargames, such as Warhammer 40K, two or more players control asymmetrical armies that include multiple units of different types and strengths. In these type of games, unit are assigned point costs, which are used to ensure that all players will control armies of similar strength. Players are provided with a total budget of points they can spend to purchase units that will be part of their army lists. Calculating the point value of individual units is a tedious manual process, which often requires long play-testing sessions and iterations of adjustments. In this paper, we propose an automated way of predicting these point costs using a linear regression approach. We use a multi-unit, turn-based, non-balanced game that has three asymmetric armies. We use Monte Carlo Tree Search agents to simulate the players, using different heuristics to emulate playing strategies. We present six different variants of our unit-point prediction algorithm, and we show how our best variant is able to almost reduce the unbalanced nature of the game by half