Generating and Adapting to Diverse Ad-Hoc Cooperation Agents in Hanabi

Hanabi is a cooperative game that brings the problem of modeling other players to the forefront. In this game, coordinated groups of players can leverage pre-established conventions to great effect, but playing in an ad-hoc setting requires agents to adapt to its partner's strategies with no previous coordination. Evaluating an agent in this setting requires a diverse population of potential partners, but so far, the behavioral diversity of agents has not been considered in a systematic way. This paper proposes Quality Diversity algorithms as a promising class of algorithms to generate diverse populations for this purpose, and generates a population of diverse Hanabi agents using MAP-Elites. We also postulate that agents can benefit from a diverse population during training and implement a simple "meta-strategy" for adapting to an agent's perceived behavioral niche. We show this meta-strategy can work better than generalist strategies even outside the population it was trained with if its partner's behavioral niche can be correctly inferred, but in practice a partner's behavior depends and interferes with the meta-agent's own behavior, suggesting an avenue for future research in characterizing another agent's behavior during gameplay.Comment: arXiv admin note: text overlap with arXiv:1907.0384

A Survey of Monte Carlo Tree Search Methods

Monte Carlo tree search (MCTS) is a recently proposed search method that combines the precision of tree search with the generality of random sampling. It has received considerable interest due to its spectacular success in the difficult problem of computer Go, but has also proved beneficial in a range of other domains. This paper is a survey of the literature to date, intended to provide a snapshot of the state of the art after the first five years of MCTS research. We outline the core algorithm's derivation, impart some structure on the many variations and enhancements that have been proposed, and summarize the results from the key game and nongame domains to which MCTS methods have been applied. A number of open research questions indicate that the field is ripe for future work

Ludo: A Case Study for Graph Transformation Tools

In this paper we describe the Ludo case, one of the case studies of the AGTIVE 2007 Tool Contest (see [22]). After summarising the case description, we give an overview of the submitted solutions. In particular, we propose a number of dimensions along which choices had to be made when solving the case, essentially setting up a solution space; we then plot the spectrum of solutions actually encountered into this solution space. In addition, there is a brief description of the special features of each of the submissions, to do justice to those aspects that are not distinguished in the general solution space

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

Mom, Dad It’s Only a Game! Perceived Gambling and Gaming Behaviors among Adolescents and Young Adults: an Exploratory Study

Gambling and gaming are increasingly popular activities among adolescents. Although gambling is illegal in Portugal for youth under the age of 18 years, gambling opportunities are growing, mainly due to similarity between gambling and other technology-based games. Given the relationship between gambling and gaming activities, the paucity of research on gambling and gaming behaviors in Portugal, and the potential negative consequences in the lives of young people, the goal of this study was to explore and compare the perceptions of these two behaviors between Portuguese adolescents and young adults. Results from six focus groups (three with adolescents and three with young adults, comprising 37 participants aged between 13 and 26 years) indicated different perceptions for the two age groups. For adolescents, gaming was associated with addiction whereas for young adults it was perceived a tool for increasing personal and social skills. With regard to gambling, adolescents associated it with luck and financial rewards, whereas young adults perceived it as an activity with more risks than benefits. These results suggest developmental differences that have implications for intervention programs and future research

Learning through play: an educational computer game to introduce radar fundamentals

The information exchange has evolved from traditional books to computers and Internet in a few years' time. Our current university students were born in this age: they learn and have fun with different methods as previous generations did. These digital natives enjoy computer games. Thus, designing games for learning some selected topics could be a good teaching strategy for such collective and also for undergraduate university students. This paper describes the development and test of an educational computer game revolving around radar. The objective of the game RADAR Technology is to teach students about the fundamentals of radar, while having fun during the learning experience. Based on the principle that you learn better what you practice, the authors want to induce students to discover a difficult to understand topic by proposing them a different experience, in a format better adapted to their generation skills. The computer game has been tested with actual students and the obtained results seem to be very promising