Physical Sciences and Mathematics Commons^™

Ai Education Matters: Data Science And Machine Learning With Magic: The Gathering, Todd W. Neller

Computer Science Faculty Publications

In this column, we briefly describe a rich dataset with many opportunities for interesting data science and machine learning assignments and research projects, we take up a simple question, and we offer code illustrating use of the dataset in pursuit of answers to the question.

Budget Magic: The Gathering For Beginners, Todd W. Neller

Computer Science Faculty Publications

In this talk, Neller overviewed budget-friendly entry points to playing Magic: The Gathering (M:TG) after its first quarter-century of success. Noting the ways in which M:TG players have applied head-designer Mark Rosewater’s “restrictions breed creativity” lesson, he celebrated their creative formats that push back against expensive “pay to win” dynamics.

Kaggle And Click-Through Rate Prediction, Todd W. Neller

Computer Science Faculty Publications

Neller presented a look at Kaggle.com, an online Data Science and Machine Learning learning community, as a place to seek rapid, experiential peer education for most any Data Science topic. Using the specific challenge of Click-Through Rate Prediction (CTRP), he focused on lessons learned from relevant Kaggle competitions on how to perform CTRP.

Getting Things Done For The Glory Of God, Todd W. Neller

Computer Science Faculty Publications

The seminar covered a fusion of David Allen’s Getting Things Done; Covey, Merrill and Merrill’s First Things First; and Matt Perman’s What’s Best Next books on time management, with a view to being a good steward of time and effort for the glory of God. More information is available at http://cs.gettysburg.edu/~tneller/resources/gtd/index.html

Mixed Logical And Probabilistic Reasoning In The Game Of Clue, Todd W. Neller, Ziqian Luo

Computer Science Faculty Publications

Neller and Ziqian Luo ’18 presented a means of mixed logical and probabilistic reasoning with knowledge in the popular deductive mystery game Clue. Using at-least constraints, we more efficiently represented and reasoned about cardinality constraints on Clue card deal knowledge, and then employed a WalkSAT-based solution sampling algorithm with a tabu search metaheuristic in order to estimate the probabilities of unknown card places.

Plentiful Possibilities For Pen, Pencil, And Paper Play, Todd W. Neller

Computer Science Faculty Publications

Neller presented games such as Dots and Boxes, Sprouts, Jotto, Chomp, and Pentominoes in order to illustrate the diversity of existing pencil and paper games. Additionally, he presented his own pencil and paper game design, Paper Penguins, and discussed the game design process.

Faith And Finance, Todd W. Neller

Computer Science Faculty Publications

The seminar covered scriptures concerning money, basic concepts of financial literacy, and a Christian perspective on investing. More information is available at http://cs.gettysburg.edu/~tneller/resources/investing/ .

Model Ai Assignments 2018, Todd W. Neller, Zack Butler, Nate Derbinsky, Heidi Furey, Fred Martin, Michael Guerzhoy, Ariel Anders, Joshua Eckroth

Computer Science Faculty Publications

The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning experience, we here present abstracts of seven AI assignments from the 2018 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http://modelai.gettysburg.edu.

Ai Education Matters: Teaching Hidden Markov Models, Todd W. Neller

Computer Science Faculty Publications

In this column, we share resources for learning about and teaching Hidden Markov Models (HMMs). HMMs find many important applications in temporal pattern recognition tasks such as speech/handwriting/gesture recognition and robot localization. In such domains, we may have a finite state machine model with known state transition probabilities, state output probabilities, and state outputs, but lack knowledge of the states generating such outputs. HMMs are useful in framing problems where external sequential evidence is used to derive underlying state information (e.g. intended words and gestures). [excerpt]

Ai Education Matters: Lessons From A Kaggle Click-Through Rate Prediction Competition, Todd W. Neller

Computer Science Faculty Publications

In this column, we will look at a particular Kaggle.com click-through rate (CTR) prediction competition, observe what the winning entries teach about this part of the machine learning landscape, and then discuss the valuable opportunities and resources this commends to AI educators and their students. [excerpt]

The Birds Of A Feather Research Challenge, Todd W. Neller

Computer Science Faculty Publications

Neller presented a set of research challenges for undergraduates that allow an excellent formative experience of research, writing, peer review, and potential presentation and publication through a top-tier conference. The focus problem is the analysis of a newly-designed solitaire card game, Birds of a Feather, so potentials for discovery abound. Open access talk slides, research code, solvability data sets, research tutorial videos, and more are also available at http://cs.gettysburg.edu/~tneller/puzzles/boaf .

Amazons, Penguins, And Amazon Penguins, Todd W. Neller

Computer Science Faculty Publications

This talk discussed a family of games based on Amazons (1988), a distant relative of Go (area control) and Chess (queen-like movement), innovated with the introduction of move obstacles. Hey! That’s My Fish! (2003) restricted the addition of obstacles and added varying points for position visits. Introducing original related game designs (e.g. Amazon Penguins (2009) and Paper Pen-guins (2009)), we demonstrated how game mechanics are like genes that mutate, crossover, and invite evolution of new games.

Playful Ai Education, Todd W. Neller

Computer Science Faculty Publications

In this talk, Neller shared how games can serve as a fun means of teaching not only game-tree search in Artificial Intelligence (AI), but also such diverse topics as constraint satisfaction, logical reasoning, planning, uncertain reasoning, machine learning, and robotics. He observed that teachers teach best when they enjoy what they share and encouraged AI educators present to teach to their unique strengths and enthusiasms.

Ai Education: Open-Access Educational Resources On Ai, Todd W. Neller

Computer Science Faculty Publications

Open-access AI educational resources are vital to the quality of the AI education we offer. Avoiding the reinvention of wheels is especially important to us because of the special challenges of AI Education. AI could be said to be “the really interesting miscellaneous pile of Computer Science”. While “artificial” is well-understood to encompass engineered artifacts, “intelligence” could be said to encompass any sufficiently difficult problem as would require an intelligent approach and yet does not fall neatly into established Computer Science subdisciplines. Thus AI consists of so many diverse topics that we would be hard-pressed to individually create quality learning …

Ai Education: Deep Neural Network Learning Resources, Todd W. Neller

Computer Science Faculty Publications

In this column, we focus on resources for learning and teaching deep neural network learning. Many exciting advances have been made in this area of late, and so many resources have become available online that the flood of relevant concepts and techniques can be overwhelming. Here, we hope to provide a sampling of high-quality resources to guide the newcomer into this booming field. [excerpt]

Ai Education: Machine Learning Resources, Todd W. Neller

Computer Science Faculty Publications

In this column, we focus on resources for learning and teaching three broad categories of machine learning (ML): supervised, unsupervised, and reinforcement learning. In ournext column, we will focus specifically on deep neural network learning resources, so if you have any resource recommendations, please email them to the address above. [excerpt]

Monte Carlo Approaches To Parameterized Poker Squares, Todd W. Neller, Zuozhi Yang, Colin M. Messinger, Calin Anton, Karo Castro-Wunsch, William Maga, Steven Bogaerts, Robert Arrington, Clay Langely

Computer Science Faculty Publications

The paper summarized a variety of Monte Carlo approaches employed in the top three performing entries to the Parameterized Poker Squares NSG Challenge competition. In all cases AI players benefited from real-time machine learning and various Monte Carlo game-tree search techniques.

Ai Education: Birds Of A Feather, Todd W. Neller

Computer Science Faculty Publications

Games are beautifully crafted microworlds that invite players to explore complex terrains that spring into existence from even simple rules. As AI educators, games can offer fun ways of teaching important concepts and techniques. Just as Martin Gardner employed games and puzzles to engage both amateurs and professionals in the pursuit of Mathematics, a well-chosen game or puzzle can provide a catalyst for AI learning and research. [excerpt]

Visualizing Fantasy Fiction: Design Of A Class In Digital Scholarship And Visualization, Including Research, Organization And Digital Visualization, That Does Not Require Programming Or It Support, Charles W. Kann

Computer Science Faculty Publications

This paper outlines a course to integrate digital visualizations into undergraduate research. These visualizations will include mapping and timelines of events, and the ability to hyperlink the events, characters, and story lines in a fantasy fiction story such as Lord of the Rings or A Game of Thrones. The digital scholarship will involve the methodology for collecting, organizing, and representing the data for the visualizations.

The topic for the visualizations in this paper is fantasy fiction; however the methods to develop these visualizations will be applicable to many academic disciplines, including the humanities and social sciences.

The paper outlines …

Pedagogical Possibilities For The 2048 Puzzle Game, Todd W. Neller

Computer Science Faculty Publications

In this paper, we describe an engaging puzzle game called 2048 and outline a variety of exercises that can leverage the game’s popularity to engage student interest, reinforce core CS concepts, and excite student curiosity towards undergraduate research. Exercises range in difficulty from CS1-level exercises suitable for exercising and assessing 1D and 2D array skills to empirical undergraduate research in Monte Carlo Tree Search methods and skilled heuristic evaluation design.

Digital Scholarship: Applying Digital Tools To Undergraduate Student Research Papers, A Proposal For A Freshman Seminar. Part I: Definition Of Student Research Methodology, Charles W. Kann

Computer Science Faculty Publications

There are many digital tools that can be used for research and presentation in nearly every college discipline, including the social sciences and humanities. These tools hold the promise to radically change both the process and products of research. But in their application these tools have failed miserably to live up to their promise.

This paper is based on the hypothesis that one reason these tools do reach their potential is that there is no systemic way to include them in research process, resulting in the tools being seen as ways to improve the final research product. This results in …

Practical Play Of The Dice Game Pig, Todd W. Neller, Clifton G.M. Presser

Computer Science Faculty Publications

The object of the jeopardy dice game Pig is to be the first player to reach 100 points. Each turn, a player repeatedly rolls a die until either a 1 is rolled or the player holds and scores the sum of the rolls (i.e., the turn total). At any time during a player’s turn, the player is faced with two choices: roll or hold. If the player rolls a 1, the player scores nothing and it becomes the opponent’s turn. If the player rolls a number other than 1, the number is added to the player’s turn total …

Pedagogical Possibilities For The N-Puzzle Problem, Zdravko Markov, Ingrid Russell, Todd W. Neller, Neli Zlatareva

Computer Science Faculty Publications

In this paper we present work on a project funded by the National Science Foundation with a goal of unifying the Artificial Intelligence (AI) course around the theme of machine learning. Our work involves the development and testing of an adaptable framework for the presentation of core AI topics that emphasizes the relationship between AI and computer science. Several hands-on laboratory projects that can be closely integrated into an introductory AI course have been developed. We present an overview of one of the projects and describe the associated curricular materials that have been developed. The project uses machine learning as …

Enhancing Undergraduate Ai Courses Through Machine Learning Projects, Ingrid Russell, Zdravko Markov, Todd W. Neller, Susan Coleman

Computer Science Faculty Publications

It is generally recognized that an undergraduate introductory Artificial Intelligence course is challenging to teach. This is, in part, due to the diverse and seemingly disconnected core topics that are typically covered. The paper presents work funded by the National Science Foundation to address this problem and to enhance the student learning experience in the course. Our work involves the development of an adaptable framework for the presentation of core AI topics through a unifying theme of machine learning. A suite of hands-on semester-long projects are developed, each involving the design and implementation of a learning system that enhances a …

Pigtail: A Pig Addendum, Todd W. Neller, Clifton G.M. Presser

Computer Science Faculty Publications

The object of the jeopardy dice game Pig is to be the first player to reach 100 points. Each turn, a player repeatedly rolls a die until either a 1 is rolled or the player holds and scores the sum of the rolls (i.e., the turn total). At any time during a player’s turn, the player is faced with two choices: roll or hold. If the player rolls a 1, the player scores nothing and it becomes the opponent’s turn. If the player rolls a number other than 1, the number is added to the player’s turn total …

Unifying An Introduction To Artificial Intelligence Course Through Machine Learning Laboratory Experiences, Ingrid Russell, Zdravko Markov, Todd W. Neller, Michael Georgiopoulos, Susan Coleman

Computer Science Faculty Publications

This paper presents work on a collaborative project funded by the National Science Foundation that incorporates machine learning as a unifying theme to teach fundamental concepts typically covered in the introductory Artificial Intelligence courses. The project involves the development of an adaptable framework for the presentation of core AI topics. This is accomplished through the development, implementation, and testing of a suite of adaptable, hands-on laboratory projects that can be closely integrated into the AI course. Through the design and implementation of learning systems that enhance commonly-deployed applications, our model acknowledges that intelligent systems are best taught through their application …

Optimal Play Of The Dice Game Pig, Todd W. Neller, Clifton G.M. Presser

Computer Science Faculty Publications

The object of the jeopardy dice game Pig is to be the first player to reach 100 points. Each player's turn consists of repeatedly rolling a die. After each roll, the player is faced with two choices: roll again, or hold (decline to roll again).

• If the player rolls a 1, the player scores nothing and it becomes the opponent's turn.
• If the player rolls a number other than 1, the number is added to the player's turn total and the player's turn continues.
• If the player holds, the turn total, the sum of the rolls during the turn, …