Checkers Program Research Articles

Study on chess game based on artificial intelligence

With the development of technology and the growth of humans needs, artificial intelligence appears to the sight of the public and wields apparent influence in this world piece by piece, especially under the scheme of automation. There are many applications of artificial intelligence, such as computer games, software design, remote controlling, online meeting and so forth. This research will base on chess and card games, and make corresponding research via pattern matching, Bayesian network and TD algorithm application, making certain analysis to mentality of human and intelligent system. A large quantity of findings has been discovered that many researchers at home and abroad are keenly interested in this field through searching for assortments of relative references, looking through previous research results and inciting part of them. Throughout the world, Alan Turing once discussed the relationship between the next stage and machine intelligence with the paper chess machine. And Arthur Samuel, one of the founders of artificial intelligence, initiated a powerful Checkers Program when he studied and worked in this field. A lot of evidence shows the fact that machine games are one of the most riveting and challenging researches in artificial intelligence. Lots of scholars make some researches for it through kinds of matches and then draw corresponding conclusions.

The Practice of the Community Pharmacists in Managing Potential Drug-Drug Interactions: A Simulated Patient Visits.

BackgroundDrug-drug interactions (DDIs) can cause treatment failure and serious adverse drug reactions, leading to morbidity and mortality. Due to their significant effects on the patient’s health, community pharmacists (CPs) competence in detecting and preventing these interactions is essential to provide optimal health services. Thus, this study aimed to explore the performance of the CPs in situations involving the presence of potential DDIs.MethodsA cross-sectional, simulated patient study was conducted in 235 community pharmacies in the Khartoum locality. Two scenarios were used to evaluate the performance of the CPs. Ten final year B. Pharm. students were selected to act as simulated patients (SPs); they were trained for two weeks to familiarize their roles. All encounters were documented immediately after leaving the pharmacy by the SPs in the data collection form.ResultsAll planned SPs visits were completed, resulting in 470 visits. None of the CPs asked about the patients’ medication history in both scenarios. After the SPs provided information about the drug used currently by the patient, 13.6% and 23.4% of the CPs had identified the potential DDIs in scenario 1 and scenario 2, respectively. In scenario 1, 59.4% distinguished the interaction of simvastatin with both drugs, while, in scenario 2, 74.5% recognized the interaction of warfarin with both drugs. In identifying DDIs, around half of the CPs were dependent on their knowledge or using drug interaction checker programs. The most common intervention made by the CPs was referring the patient to the prescriber (56.3% CPs in scenario 1 and 60% CPs in scenario 2).ConclusionCPs practice in identifying and managing potential DDIs was poor. The current CPs practices need substantial improvement. Therefore, professional education and the use of software programs in community pharmacies should be encouraged.

Evaluation of drug-drug interactions and their clinical importance in a pediatric hematopoietic stem cell transplantation unit

Background and Aims: Many drugs with narrow therapeutic range and high toxicity risk are used in hematopoietic stem cell transplantation (HSCT) Units. The increase in the number of drugs raises the likelihood of interactions. This is particularly important in pediatric patients and may adversely affect the treatment process. In this study, we aimed to determine the potential drug interactions and to evaluate the clinical significance of them in terms of physician’s and pharmacist’s perceptions. Methods: The study was conducted as a prospective descriptive study over a six-month period in a tertiary care hospital’s Pediatric HSCT Unit. A pharmacist evaluated inpatients’ drugs for drug interactions by using a drug interaction checker program and the clinical significance of the interactions were evaluated by the physician and the pharmacist separately. Results: Drugs used in 20 patients (median age= 8 years, range= 0.6–17 years) were evaluated. A total of 525 potential drugdrug interactions were identified. Two hundred and forty seven interactions (47.05%) were major; 238 (45.33%) were moderate; 23 (4.38%) were contraindicated. The number of the interactions considered “clinically significant” by the pharmacist and “clinically insignificant” by the physician at the preparative regimen and post-transplant period were 15 (35.7%) and 37 (29.4%), respectively. Conclusion: The management of drug interactions is important in pediatric HSCT patients as a vulnerable group. Drug interactions should be interpreted according to the patient's clinical presentation, not only theoretically. Cooperation between physicians and pharmacists in the management of interactions will contribute to optimize the patient's treatment.

Homogeneous Group Performance and Stability in Checkers

Experiments on groups of Checkers programs, playing by majority voting, were performed to investigate performance and stability. Homogeneous groups, copies of the same program, was used to perform these experiments instead of heterogeneous group that was more complicated by factors of different programs. Experiments were performed based on a search-depth of 5, 10 and 12 using the Samuel checkers program. Games of checkers were played between groups of size ranging from 1 up to 10 for each side. Experiment results suggest that group performance increases as a kind of logarithm function as the group size gradually increases for stronger player, and the performance slowly decreases in the case of a weaker player, stability seems to increase as the group size increases.

An integrated environment for Spin-based C code checking

Model-driven code checking (MDCC) has been successfully used for the verification of functional requirements of C code. An environment model that describes the context, which a program is expected to run in, is defined in Promela, translated to a model checker program by Spin, and linked with the program acting as system under verification. In this article, we summarise the practical advantages of MDCC which motivate its use in an industrial setting and discuss the challenges to its broader adoption. Environment models exhibit heavily intertwined Promela and C code statements, which make them hard to write and understand. We propose a high-level language for verification harness definition which hides the Spin engine under the hood. A small number of language concepts is sufficient to define verification harnesses for commonly encountered C programs. Widening the scope of the approach, we provide means to verify programs that exhibit internal state and extend the set of checked properties beyond classical assertions to those checked by LLVM/Clang code sanitizers. Thus, a user can focus on finding the best solution to combine exhaustive exploration of the environment with testing strategies. Our approach is prototypically integrated into mbeddr development platform. We present its instantiation on real-world code examples and discuss our experiences gained with the verification of software from the railway domain.

The Importance of Computerized Drug Interaction Checker Programs to Avoid Potential Drug Interactions Used in Community Pharmacies: A Preliminary Study with Clarithromycin

The Importance of Computerized Drug Interaction Checker Programs to Avoid Potential Drug Interactions Used in Community Pharmacies: A Preliminary Study with Clarithromycin

The Importance of Computerized Drug Interaction Checker Programs Used in Community Pharmacies to Avoid Potential Drug Interactions: A Preliminary Study with Clarithromycin

The Importance of Computerized Drug Interaction Checker Programs Used in Community Pharmacies to Avoid Potential Drug Interactions: A Preliminary Study with Clarithromycin

Monitoring Young Tree Survival with Citizen Scientists: The Evolving Tree Checkers Program in Philadelphia, PA

Citizen science programs are not static; they change over time in response to new program priorities and emerging technologies, as well as to improve work flow for program staff and volunteers. In this article, the authors present a case study of an evolving urban forestry citizen science program at the Pennsylvania Horticultural Society, a nonprofit organization in Philadelphia, Pennsylvania, U.S. The Tree Checkers program involves tree stewards recording data each summer about recently planted tree survival, growth, crown vigor, and maintenance, while also engaging their neighbors to encourage proper tree care. The program began in 2011, but changed in 2016 to use a new online data collection tool that was integrated into a larger tree data management system. Tree Checkers has also shifted to be more focused on rigorous data to report program performance and share information with researchers, whereas the earlier years of Tree Checkers were centered on enabling and encouraging neighborhood tree stewards to plan for tree care. A recent data quality evaluation showed that volunteer data was reasonably consistent with data reported by more experienced interns for tree survival, vigor, and trunk measurements, but stewardship variables were not interpreted and recorded consistently. By making rigorous data more central to Tree Checkers, program staff also sought to institutionalize monitoring within the organization, allowing for direct comparisons of outcomes year-to-year. The authors close with lessons learned that are relevant to other organizations seeking to create or enhance outcomes monitoring programs with citizen scientists.

The Importance of Computerized Drug Interaction Checker Programs to Avoid Potential Drug-Drug Interactions used in Community Pharmacies: A Preliminary Study with Clarithromycin

The Importance of Computerized Drug Interaction Checker Programs to Avoid Potential Drug-Drug Interactions used in Community Pharmacies: A Preliminary Study with Clarithromycin

How Accurate Are Patients at Diagnosing the Cause of Their Knee Pain With the Help of a Web-based Symptom Checker?

Background:Researching medical information is the third most popular activity online, and there are a variety of web-based symptom checker programs available.Purpose:This study evaluated a patient’s ability to self-diagnose their knee pain from a list of possible diagnoses supplied by an accurate symptom checker.Study Design:Cohort study (diagnosis); Level of evidence, 2.Methods:All patients older than 18 years who presented to the office of 7 different fellowship-trained sports medicine surgeons over an 8-month period with a complaint of knee pain were asked to participate. A web-based symptom checker for knee pain was used; the program has a reported accuracy of 89%. The symptom checker generates a list of potential diagnoses after patients enter symptoms and links each diagnosis to informative content. After exploring the informative content, patients selected all diagnoses they felt could explain their symptoms. Each patient was later examined by a physician who was blinded to the differential generated by the program as well as the patient-selected diagnoses. A blinded third party compared the diagnoses generated by the program with those selected by the patient as well as the diagnoses determined by the physician. The level of matching between the patient-selected diagnoses and the physician’s diagnoses determined the patient’s ability to correctly diagnose their knee pain.Results:There were 163 male and 165 female patients, with a mean age of 48 years (range, 18-76 years). The program generated a mean 6.6 diagnoses (range, 2-15) per patient. Each patient had a mean 1.7 physician diagnoses (range, 1-4). Patients selected a mean 2 diagnoses (range, 1-9). The patient-selected diagnosis matched the physician’s diagnosis 58% of the time.Conclusion:With the aid of an accurate symptom checker, patients were able to correctly identify the cause of their knee pain 58% of the time.

How Accurate Are Patients At Diagnosing The Cause Of Their Knee Pain With The Help Of A Web-based Symptom Checker?

Objectives:Researching medical information is the third most popular activity online, and there are a variety of web-based symptom checker programs available to the patient. A recent study has demonstrated that a web-based program can generate an accurate differential diagnosis in 89% of ambulatory patients with knee pain based on a history entered by the patient. Despite the regularity of online symptom checking, the authors are not aware of any study that has evaluated a patient's ability to self-diagnose the cause of their knee pain based on the results of a diagnostic program. The purpose of this study was to determine the ability of a patient to select his or her own diagnosis after being supplied with a differential diagnosis generated by a web-based program for the patient's knee pain.Methods:A web-based program was created to collect a knee pain history and generate a differential diagnosis for ambulatory patients with knee pain. The diagnoses generated by the program were linked to informative content which was immediately available to the patient in order to allow them to learn more about each diagnosis. Prior to coming to their office appointment, the patient was given the link for the program. They entered their history into the program which then generated a list of most likely causes for the patient's knee pain based on their history. The program has the capability of generating 21 common knee diagnoses. After exploring the informative content, the patient selected which diagnosis or diagnoses they believed were the most likely cause of their pain. Despite the program generating a limited list, the patient had the ability to select from all 21 diagnoses capable of being generated by the program when selecting the diagnosis(es) they believed was the cause of their knee pain. Within days of completing the program, each patient was examined by a board-certified orthopaedic surgeon. The physician was blinded to the differential diagnosis generated by the program as well as the diagnosis(es) selected by the patient. A third party was responsible for comparing the diagnosis(es) generated by the program with that selected by the patient as well as the final diagnosis(es) determined by the physician. The diagnosis(es) provided by the physician were considered the correct diagnosis for the patient. The level of matching between the patient selected diagnosis and the physician's diagnosis determined the ability of the patient to correctly diagnose the cause of their knee pain.Results:Ninety-two males and 108 females, with an average age of 49 years (19-76) were analyzed for this study. Two hundred twenty-seven patients were excluded from analysis because they did not complete the entire program, 10 patients were excluded because they were under 18 years of age and 6 patients were excluded because they had a diagnosis other than one capable of being generated by the program. Patients selected an average of 2 diagnoses (1-9). The program generated an average of 6.6 diagnoses (2-13) per patient and each patient had an average of 1.8 physician diagnoses (1-4). The patient selected diagnosis matched the physician's diagnosis 58% of the time.Conclusion:Patients are able to diagnose the cause of their knee pain 58% of the time based on information provided by a web-based symptom checker program.

Using Comparative Genomics to Study DNA Sequences of the Muller F Element from Drosophila biarmipes

The Genomics Education Partnership* (GEP) is a scientific and educational partnership using comparative genomics to characterize the Muller F element, a distinct chromosomal domain, from the genomes of several Drosophila species (see www.gep.wustl.edu). In Drosophila melanogaster, the F element corresponds to the fourth chromosome (or “dot” chromosome), which appears to be heterochromatic by many criteria, but has a relatively high gene density. Our goal is to study the evolution of these sequences to further our understanding of the function of heterochromatin. As part of an advanced genetics course at Albion College, we used several web-based tools to annotate a 50,000 base pair contiguous sequence from the genome of Drosophila biarmipes. The annotation process involved using the corresponding genomic region of the Drosophila melanogaster fourth chromosome as a reference sequence. Using BLAST we estimated the positions of each exon, then using a variety of evidence tracks from the UCSC genome browser, we precisely localized start codons, donor and acceptor splice sites, and stop codons for each isoform. Gene models were verified using the Gene Model Checker program and by generating final sequence alignments and dot plots using BLAST. Our analysis resulted in the annotation of five distinct genes in this contig. The genes ranged in complexity from 2-7 splice variants, with individual isoforms ranging in size from 4 to 12 exons each. Our analysis will be combined with data from other student members of the partnership to help answer questions about the organization and function of the Muller F element in several different species. *The Genomics Education Partnership is funded by HHMI (Professors grant #52007051 to SCR Elgin) and by Washington University in St. Louis (WUSTL).

The Realization of Genetic Algorithm in Terms of Checkers Evaluation Function

The GA(Genetic Algorithm) is used in this paper to solve the evaluation problem in the checkers game. The evaluation parameter is chosen based on six critical facts, such as the number of black pieces and the number of red pieces. The evaluation function is linear with different weights. Using the weights as the chromosome, along with the local hill-climbing method in GA and the mathematical statistical method to choose child generation, the algorithm realizes evolution automatically. With sufficient evolution times, new chromosome appears, leading to the formation of an optimized evaluation function. Based on the experimental data analysis, the algorithm could enhance the power of checkers program effectively.

Medication therapy management (MTM) in a multidisciplinary supportive oncology clinic.

30 Background: Patients with advanced cancer experience significant symptom burden and psychosocial distress from the onset of their diagnosis and throughout treatment shifting the paradigm of supportive care. In addition, most cancer patients have multiple co-morbidities and are at high risk of poly-pharmacy. One in three ambulatory cancer patients are at risk of drug-drug interactions. Methods: In June 2010, a multidisciplinary supportive oncology clinic, modeled after the Massachusetts General Hospital article by Temel et al., was started and staffed by a pharmacist, a nurse, a social worker and a dietitian and lead by a nurse practitioner. A chart audit was conducted for all patients seen in the clinic between June 2010 and March 2012. Pharmacy assessment entries were evaluated for diagnosis, medication issues and total time spent with patients. Duplicate therapy was defined as an unnecessary duplication in therapy for a single symptom and/or two medications in the same class. Drug-Interactions were assessed utilizing Micromedex 2.0 Drug-Interaction Checker and Lexicomp Lexi-Interact Online drug-interaction analysis program. All major kinetic interactions were recorded and pharmacodynamic interactions were recorded if they required intervention. Results: From June 2010 to May 2012, 153 patients were seen in the clinic. The most common diagnoses were pancreatic, lung, breast and head and neck. Use of a standardized pharmacy assessment identified duplicate therapies in 45.1% of patients, drug-drug interactions in 35.3%, side-effects in 83%, lack of efficacy in 88.9% and untreated conditions 68.6%. The pharmacists spent an average of 44.1 minutes (range 15-90 min) with patients. Conclusions: Pharmacist-initiated MTM identifies a higher rate of poly-pharmacy, drug-drug interactions and side effects than found in literature. Identification allows for referral to other disciplines within the clinic for work-up. Gastrointestinal related issues were referred to a dietitian, psychosocial issues including adherence issues to a social worker and medication related issues to the nurse practitioner for follow-up. Initial identification of these issues has allowed for more long-term follow-up in these patients.

Introducing Individual and Social Learning Into Evolutionary Checkers

In recent years, much research attention has been paid to evolving self-learning game players. Fogel's Blondie24 is just one demonstration of a real success in this field and it has inspired many other scientists. In this paper, evolutionary neural networks, evolved via an evolution strategy, are employed to evolve game-playing strategies for the game of Checkers. In addition, we introduce an individual and social learning mechanism into the learning phase of this evolutionary Checkers system. The best player obtained is tested against an implementation of an evolutionary Checkers program, and also against a player, which has been evolved within a round robin tournament. The results are promising and demonstrate that using individual and social learning enhances the learning process of the evolutionary Checkers system and produces a superior player compared to what was previously possible.

Introduction to Special Section on Evolutionary Computation in Games

Ever since the dawn of artificial intelligence in the 1950s, games have been part and parcel of this lively field. In 1957, a year after the Dartmouth Conference that marked the official birth of AI, Alex Bernstein designed a program for the IBM 704 that played two amateur games of chess. In 1958, Allen Newell, J. C. Shaw, and Herbert Simon introduced a more sophisticated chess program (beaten in 35 moves by a 10-year-old beginner in its last official game played in 1960). Arthur L. Samuel of IBM spent much of the fifties working on game-playing AI programs, and by 1961 he had a checkers program that could play rather decently. In 1961 and 1963 Donald Michie described a simple trial-and-error learning system for learning how to play Tic-Tac-Toe (or Noughts and Crosses) called MENACE (for Matchbox Educable Noughts and Crosses Engine). These are but examples of highly popular games that have been treated by AI researchers since the field’s inception. ‘‘There are two principal reasons to continue to do research on games,’’ wrote Epstein [1]. ‘‘First, human fascination with game playing is long-standing and pervasive. Anthropologists have catalogued popular games in almost every culture... Games intrigue us because they address important cognitive functions... The second reason to continue game-playing research is that some difficult games remain to be won, games that people play very well but computers do not. These games clarify

Arabic GramCheck: a grammar checker for Arabic: Research Articles

Arabic is a Semitic language that is rich in its morphology and syntax. The very numerous and complex grammar rules of the language may be confusing for the average user of a word processor. In this paper, we report our attempt at developing a grammar checker program for Modern Standard Arabic, called Arabic GramCheck. Arabic GramCheck can help the average user by checking hissher writing for certain common grammatical errors; it describes the problem for himsher and offers suggestions for improvement. The use of the Arabic grammatical checker can increase productivity and improve the quality of the text for anyone who writes Arabic. Arabic GramCheck has been successfully implemented using SICStus Prolog on an IBM PC. The current implementation covers a well-formed subset of Arabic and focuses on people trying to write in a formal style. Successful tests have been performed using a set of Arabic sentences. It is concluded that the approach is promising by observing the results as compared to the output of a commercially available Arabic grammar checker. Copyright © 2005 John Wiley & Sons, Ltd.

Arabic GramCheck: a grammar checker for Arabic

Arabic is a Semitic language that is rich in its morphology and syntax. The very numerous and complex grammar rules of the language may be confusing for the average user of a word processor. In this paper, we report our attempt at developing a grammar checker program for Modern Standard Arabic, called Arabic GramCheck. Arabic GramCheck can help the average user by checking his/her writing for certain common grammatical errors; it describes the problem for him/her and offers suggestions for improvement. The use of the Arabic grammatical checker can increase productivity and improve the quality of the text for anyone who writes Arabic. Arabic GramCheck has been successfully implemented using SICStus Prolog on an IBM PC. The current implementation covers a well-formed subset of Arabic and focuses on people trying to write in a formal style. Successful tests have been performed using a set of Arabic sentences. It is concluded that the approach is promising by observing the results as compared to the output of a commercially available Arabic grammar checker. Copyright © 2005 John Wiley & Sons, Ltd.

Verifying Anaconda's expert rating by competing against Chinook: experiments in co-evolving a neural checkers player

Since the early days of artificial intelligence, there has been interest in having a computer teach itself how to play a game of skill, like checkers, at a level that is competitive with human experts. To be truly noteworthy, such efforts should minimize the amount of human intervention in the learning process. Recently, co-evolution has been used to evolve a neural network (called Anaconda) that, when coupled with a minimax search, can evaluate checker-boards and play to the level of a human expert, as indicated by its rating of 2045 on an international web site for playing checkers. The neural network uses only the location, type, and number of pieces on the board as input. No other features that would require human expertise are included. Experiments were conducted to verify the neural network's expert rating by competing it in 10 games against a “novice-level” version of Chinook, a world-champion checkers program. The neural network had 2 wins, 4 losses, and 4 draws in the 10-game match. Based on an estimated rating of Chinook at the novice level, the results corroborate Anaconda's expert rating.

The Effectiveness of Word Processor Spell Checker Programs to Produce Target Words for Misspellings Generated by Students with Learning Disabilities

This study investigated spell check programs to determine how they differ in producing target words in first position in the replacement list for misspellings generated by students with learning disabilities. A pool of 1,008 misspellings taken from 111 writing samples generated by students with learning disabilities, grades three through eight, were spell checked by the spell check function of nine word processing software programs. Misspellings were classified by the level of phonetic mismatch to the target word (phonetic error level) and the proportion of correct two-letter sequences (bigram ratio). A significant difference was found among spell checkers in their ability to produce target words first in the replacement list. In addition, a significant difference with respect to phonetic error level and bigram ratio was found. Efficiency of spell checkers increased as the phonetic error level or the bigram ratio of the misspellings increased. These results suggest that spell checkers are overall ineffective in producing target words first in the replacement list for misspellings generated by students with learning disabilities.