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

Vision Transformers for Computer Go

Motivated by the success of transformers in various fields, such as language understanding and image analysis, this investigation explores their application in the context of the game of Go. In particular, our study focuses on the analysis of the Transformer in Vision. Through a detailed analysis of numerous points such as prediction accuracy, win rates, memory, speed, size, or even learning rate, we have been able to highlight the substantial role that transformers can play in the game of Go. This study was carried out by comparing them to the usual Residual Networks

Should It Stay or Should It Go?: Exploring the potential for structural reform in Milwaukee County government

Milwaukee County government faces immediate and substantial fiscal and programmatic challenges. The county's structural deficit -- defined as the gap between expenditure needs and anticipated revenues -- is projected to grow from $48 million in 2011 to more than$106 million by 2014, despite several successive years of significant expenditure and staff reductions and anticipation of significant wage and benefit concessions in 2010. This projection is the clearest indication yet that the county's finances are crumbling and that valued services in areas like parks, transit, mental health and public safety face severe degradation without prompt and concerted action. This action could take any of several forms, including the complete elimination of Milwaukee County government. This report, commissioned by the Greater Milwaukee Committee, provides detailed analysis and perspective on the complex issues surrounding that option, as well as other potential structural changes

Psychosocial interventions for people with dementia: a synthesis of systematic reviews

Objectives: Over the last 10 years there has been a multitude of studies of psychosocial interventions for people with dementia. However, clinical services face a dilemma about which intervention should be introduced into clinical practice because of the inconsistency in some of the findings between different studies and the differences in the study qualities and trustworthiness of evidence. There was a need to provide a comprehensive summary of the best evidence to illustrate what works. Methods: A review of the systematic reviews of psychosocial interventions in dementia published between January 2010 and February 2016 was conducted. Results: Twenty-two reviews (8 physical, 7 cognitive, 1 physical/cognitive and 6 other psychosocial interventions) with a total of 197 unique studies met the inclusion criteria. Both medium to longer-term multi-component exercise of moderate to high intensity, and, group cognitive stimulation consistently show benefits. There is not sufficient evidence to determine whether psychological or social interventions might improve either mood or behaviour due to the heterogeneity of the studies and interventions included in the reviews. Conclusion: There is good evidence that multi-component exercise with sufficient intensity improves global physical and cognitive functions and activities of daily living skills. There is also good evidence that group based cognitive stimulation improves cognitive functions, social interaction and quality of life. This synthesis also highlights the potential importance of group activities to improve social integration for people with dementia. Future research should investigate longer-term specific outcomes, consider the severity and types of dementia, and investigate mechanisms of change

Monte Carlo Tree Search based Hybrid Optimization of Variational Quantum Circuits

Variational quantum algorithms stand at the forefront of simulations on near-term and future fault-tolerant quantum devices. While most variational quantum algorithms involve only continuous optimization variables, the representational power of the variational ansatz can sometimes be significantly enhanced by adding certain discrete optimization variables, as is exemplified by the generalized quantum approximate optimization algorithm (QAOA). However, the hybrid discrete-continuous optimization problem in the generalized QAOA poses a challenge to the optimization. We propose a new algorithm called MCTS-QAOA, which combines a Monte Carlo tree search method with an improved natural policy gradient solver to optimize the discrete and continuous variables in the quantum circuit, respectively. We find that MCTS-QAOA has excellent noise-resilience properties and outperforms prior algorithms in challenging instances of the generalized QAOA

Recent Advances in General Game Playing

The goal of General Game Playing (GGP) has been to develop computer programs that can perform well across various game types. It is natural for human game players to transfer knowledge from games they already know how to play to other similar games. GGP research attempts to design systems that work well across different game types, including unknown new games. In this review, we present a survey of recent advances (2011 to 2014) in GGP for both traditional games and video games. It is notable that research on GGP has been expanding into modern video games. Monte-Carlo Tree Search and its enhancements have been the most influential techniques in GGP for both research domains. Additionally, international competitions have become important events that promote and increase GGP research. Recently, a video GGP competition was launched. In this survey, we review recent progress in the most challenging research areas of Artificial Intelligence (AI) related to universal game playing