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The act and experience of programming is, at its heart, a fundamentally human activity that results in the production of artifacts. When considering programming, therefore, it would be a glaring omission to not involve people who specialize…

Software Engineering · Computer Science 2018-11-07 John Aycock , Tara Copplestone

We consider a probabilistic version of the depth-first search on mazes with two exits, and show that this algorithm has equal probability of finding either exit. The proof is combinatorial and uses an explicit involution.

Combinatorics · Mathematics 2024-08-07 Nikita Gladkov , Igor Pak

In this paper we introduce and investigate a new type of automata which turns out to be rich in deep and complex phenomena. For our model, a maze is a countable strongly connected digraph called the board together with a proper colouring of…

Combinatorics · Mathematics 2018-04-17 Stefan David , Marius Tiba

At the 2017 Artificial and Computational Intelligence in Games meeting at Dagstuhl, Julian Togelius asked how to make spaces where every way of filling in the details yielded a good game. This study examines the possibility of enriching…

Artificial Intelligence · Computer Science 2019-06-11 Daniel Ashlock , Christoph Salge

Node embedding algorithms produce low-dimensional latent representations of nodes in a graph. These embeddings are often used for downstream tasks, such as node classification and link prediction. In this paper, we investigate the following…

Machine Learning · Computer Science 2024-06-13 Zohair Shafi , Ayan Chatterjee , Tina Eliassi-Rad

Despite the huge empirical success of deep learning, theoretical understanding of neural networks learning process is still lacking. This is the reason, why some of its features seem "mysterious". We emphasize two mysteries of deep…

Machine Learning · Computer Science 2019-05-20 Eugene Golikov

The opaqueness of many complex machine learning algorithms is often mentioned as one of the main obstacles to the ethical development of artificial intelligence (AI). But what does it mean for an algorithm to be opaque? Highly complex…

Machine Learning · Computer Science 2025-08-20 Andrés Páez

Based on the rules of magic cubes, a game of two-dimensional magic cube was deliberately designed. This essay will explore its properties with the assistance of group theory and computer programming. It will first elaborate the rules of…

Group Theory · Mathematics 2018-11-09 Qixuan Zhang , Zihan Jia , Yuming Xiang

A myriad of different Large Language Models (LLMs) face a common challenge in contextually analyzing table question-answering tasks. These challenges are engendered from (1) finite context windows for large tables, (2) multi-faceted…

Artificial Intelligence · Computer Science 2024-06-18 William Watson , Nicole Cho , Tucker Balch , Manuela Veloso

This study introduces a novel theoretical framework, the Stacked Autoencoder Evolution Hypothesis, which proposes that biological evolutionary systems operate through multi-layered self-encoding and decoding processes, analogous to stacked…

Neural and Evolutionary Computing · Computer Science 2026-02-03 Hiroyuki Iizuka

This article aims to explain the Nested Benders algorithm for the solution of large-scale stochastic programming problems in a way that is intelligible to someone coming to it for the first time. In doing so it gives an explanation of…

Optimization and Control · Mathematics 2013-12-13 James Murphy

We study quantum algorithms on search trees of unknown structure, in a model where the tree can be discovered by local exploration. That is, we are given the root of the tree and access to a black box which, given a vertex $v$, outputs the…

Quantum Physics · Physics 2022-12-29 Andris Ambainis , Martins Kokainis

Exciting contemporary machine learning problems have recently been phrased in the classic formalism of tree search -- most famously, the game of Go. Interestingly, the state-space underlying these sequential decision-making problems often…

Machine Learning · Computer Science 2021-06-17 Julia Grosse , Cheng Zhang , Philipp Hennig

New algorithms for generating closed knight's tours are obtained by generating a vertex-disjoint cycle cover of the knight's graph and joining the resulting cycles. It is shown experimentally that these algorithms are significantly faster…

Discrete Mathematics · Computer Science 2020-01-20 Ian Parberry

The apparent ``black box'' nature of neural networks is a barrier to adoption in applications where explainability is essential. This paper presents TAME (Trainable Attention Mechanism for Explanations), a method for generating explanation…

Computer Vision and Pattern Recognition · Computer Science 2025-01-30 Mariano Ntrougkas , Nikolaos Gkalelis , Vasileios Mezaris

Our goal, in the context of open-domain textual question-answering (QA), is to explain answers by showing the line of reasoning from what is known to the answer, rather than simply showing a fragment of textual evidence (a "rationale'"). If…

Computation and Language · Computer Science 2022-05-31 Bhavana Dalvi , Peter Jansen , Oyvind Tafjord , Zhengnan Xie , Hannah Smith , Leighanna Pipatanangkura , Peter Clark

The emergence of tools based on artificial intelligence has also led to the need of producing explanations which are understandable by a human being. In most approaches, the system is considered a black box, making it difficult to generate…

Artificial Intelligence · Computer Science 2024-10-23 Germán Vidal

Games have always been a popular test bed for artificial intelligence techniques. Game developers are always in constant search for techniques that can automatically create computer games minimizing the developer's task. In this work we…

Neural and Evolutionary Computing · Computer Science 2014-06-03 Zahid Halim

Bob hides a ball in one of four drawers. Alice is to locate it. Classically she has to open up to three drawers, quantally just one. The fundamental reason for this quantum speedup is not known. The usual representation of the quantum…

Quantum Physics · Physics 2015-08-20 Giuseppe Castagnoli

Transformer models underpin many recent advances in practical machine learning applications, yet understanding their internal behavior continues to elude researchers. Given the size and complexity of these models, forming a comprehensive…

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