Improving Search with Supervised Learning in Trick-Based Card Games

In trick-taking card games, a two-step process of state sampling and evaluation is widely used to approximate move values. While the evaluation component is vital, the accuracy of move value estimates is also fundamentally linked to how well the sampling distribution corresponds the true distribution. Despite this, recent work in trick-taking card game AI has mainly focused on improving evaluation algorithms with limited work on improving sampling. In this paper, we focus on the effect of sampling on the strength of a player and propose a novel method of sampling more realistic states given move history. In particular, we use predictions about locations of individual cards made by a deep neural network --- trained on data from human gameplay - in order to sample likely worlds for evaluation. This technique, used in conjunction with Perfect Information Monte Carlo (PIMC) search, provides a substantial increase in cardplay strength in the popular trick-taking card game of Skat.Comment: Accepted for publication at AAAI-1

Capabilities of wind tunnels with two-adaptive walls to minimize boundary interference in 3-D model testing

An initial wind tunnel test was made to validate a new wall adaptation method for 3-D models in test sections with two adaptive walls. First part of the adaptation strategy is an on-line assessment of wall interference at the model position. The wall induced blockage was very small at all test conditions. Lift interference occurred at higher angles of attack with the walls set aerodynamically straight. The adaptation of the top and bottom tunnel walls is aimed at achieving a correctable flow condition. The blockage was virtually zero throughout the wing planform after the wall adjustment. The lift curve measured with the walls adapted agreed very well with interference free data for Mach 0.7, regardless of the vertical position of the wing in the test section. The 2-D wall adaptation can significantly improve the correctability of 3-D model data. Nevertheless, residual spanwise variations of wall interference are inevitable

cDNA and Gene Analyses Imply a Novel Structure for a Rat Carcinoembryonic Antigen-related Protein

The gene encoding the human tumor marker carcinoembryonic antigen (CEA) belongs to a gene family which can be subdivided into the CEA and the pregnancy-specific glycoprotein subgroups. The corresponding proteins are members of the immunoglobulin superfamily, characterized through the presence of one IgV-like domain and a varying number of IgC-like domains. Since the function of the CEA family is not well understood, we decided to establish an animal model in the rat to study its tissue- specific and developmental stage-dependent expression. To this end, we have screened an 18-day rat placenta cDNA library with a recently isolated fragment of a rat CEA-related gene. Two overlapping clones containing the complete coding region for a putative 709 amino acid protein (rnCGM1; Mr = 78,310) have been characterized. In contrast to all members of the human CEA family, this rat CEA-related protein consists of five IgV-like domains and only one IgC-like domain. This novel structure, which has been confirmed at the genomic level might have important functional implications. Due to the rapid evolutionary divergence of the rat and human CEA gene families it is not possible to assign rnCGM1 to its human counterpart. However, the predominant expression of the rnCGM1 gene in the placenta suggests that it could be analogous to one of the human pregnancy-specific glycoprotein genes

Procedures for Computing Transonic Flows for Control of Adaptive Wind Tunnels

Numerical methods are developed for control of three dimensional adaptive test sections. The physical properties of the design problem occurring in the external field computation are analyzed, and a design procedure suited for solution of the problem is worked out. To do this, the desired wall shape is determined by stepwise modification of an initial contour. The necessary changes in geometry are determined with the aid of a panel procedure, or, with incident flow near the sonic range, with a transonic small perturbation (TSP) procedure. The designed wall shape, together with the wall deflections set during the tunnel run, are the input to a newly derived one-step formula which immediately yields the adapted wall contour. This is particularly important since the classical iterative adaptation scheme is shown to converge poorly for 3D flows. Experimental results obtained in the adaptive test section with eight flexible walls are presented to demonstrate the potential of the procedure. Finally, a method is described to minimize wall interference in 3D flows by adapting only the top and bottom wind tunnel walls