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

Reconciling timber extraction with biodiversity conservation in tropical forests using reduced-impact logging

Over 20% of the world's tropical forests have been selectively logged, and large expanses are allocated for future timber extraction. Reduced-impact logging (RIL) is being promoted as best practice forestry that increases sustainability and lowers CO2 emissions from logging, by reducing collateral damage associated with timber extraction. RIL is also expected to minimize the impacts of selective logging on biodiversity, although this is yet to be thoroughly tested. We undertake the most comprehensive study to date to investigate the biodiversity impacts of RIL across multiple taxonomic groups. We quantified birds, bats and large mammal assemblage structures, using a before-after control-impact (BACI) design across 20 sample sites over a 5-year period. Faunal surveys utilized point counts, mist nets and line transects and yielded >250 species. We examined assemblage responses to logging, as well as partitions of feeding guild and strata (understorey vs. canopy), and then tested for relationships with logging intensity to assess the primary determinants of community composition. Community analysis revealed little effect of RIL on overall assemblages, as structure and composition were similar before and after logging, and between logging and control sites. Variation in bird assemblages was explained by natural rates of change over time, and not logging intensity. However, when partitioned by feeding guild and strata, the frugivorous and canopy bird ensembles changed as a result of RIL, although the latter was also associated with change over time. Bats exhibited variable changes post-logging that were not related to logging, whereas large mammals showed no change at all. Indicator species analysis and correlations with logging intensities revealed that some species exhibited idiosyncratic responses to RIL, whilst abundance change of most others was associated with time. Synthesis and applications. Our study demonstrates the relatively benign effect of reduced-impact logging (RIL) on birds, bats and large mammals in a neotropical forest context, and therefore, we propose that forest managers should improve timber extraction techniques more widely. If RIL is extensively adopted, forestry concessions could represent sizeable and important additions to the global conservation estate – over 4 million km2

Testing robustness of relative complexity measure method constructing robust phylogenetic trees for Galanthus L. Using the relative complexity measure

Background: Most phylogeny analysis methods based on molecular sequences use multiple alignment where the quality of the alignment, which is dependent on the alignment parameters, determines the accuracy of the resulting trees. Different parameter combinations chosen for the multiple alignment may result in different phylogenies. A new non-alignment based approach, Relative Complexity Measure (RCM), has been introduced to tackle this problem and proven to work in fungi and mitochondrial DNA. Result: In this work, we present an application of the RCM method to reconstruct robust phylogenetic trees using sequence data for genus Galanthus obtained from different regions in Turkey. Phylogenies have been analyzed using nuclear and chloroplast DNA sequences. Results showed that, the tree obtained from nuclear ribosomal RNA gene sequences was more robust, while the tree obtained from the chloroplast DNA showed a higher degree of variation. Conclusions: Phylogenies generated by Relative Complexity Measure were found to be robust and results of RCM were more reliable than the compared techniques. Particularly, to overcome MSA-based problems, RCM seems to be a reasonable way and a good alternative to MSA-based phylogenetic analysis. We believe our method will become a mainstream phylogeny construction method especially for the highly variable sequence families where the accuracy of the MSA heavily depends on the alignment parameters

Consistency and convergence rate of phylogenetic inference via regularization

It is common in phylogenetics to have some, perhaps partial, information about the overall evolutionary tree of a group of organisms and wish to find an evolutionary tree of a specific gene for those organisms. There may not be enough information in the gene sequences alone to accurately reconstruct the correct "gene tree." Although the gene tree may deviate from the "species tree" due to a variety of genetic processes, in the absence of evidence to the contrary it is parsimonious to assume that they agree. A common statistical approach in these situations is to develop a likelihood penalty to incorporate such additional information. Recent studies using simulation and empirical data suggest that a likelihood penalty quantifying concordance with a species tree can significantly improve the accuracy of gene tree reconstruction compared to using sequence data alone. However, the consistency of such an approach has not yet been established, nor have convergence rates been bounded. Because phylogenetics is a non-standard inference problem, the standard theory does not apply. In this paper, we propose a penalized maximum likelihood estimator for gene tree reconstruction, where the penalty is the square of the Billera-Holmes-Vogtmann geodesic distance from the gene tree to the species tree. We prove that this method is consistent, and derive its convergence rate for estimating the discrete gene tree structure and continuous edge lengths (representing the amount of evolution that has occurred on that branch) simultaneously. We find that the regularized estimator is "adaptive fast converging," meaning that it can reconstruct all edges of length greater than any given threshold from gene sequences of polynomial length. Our method does not require the species tree to be known exactly; in fact, our asymptotic theory holds for any such guide tree.Comment: 34 pages, 5 figures. To appear on The Annals of Statistic