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Wagering mechanisms are one-shot betting mechanisms that elicit agents' predictions of an event. For deterministic wagering mechanisms, an existing impossibility result has shown incompatibility of some desirable theoretical properties. In…

Computer Science and Game Theory · Computer Science 2022-03-31 Yiling Chen , Yang Liu , Juntao Wang

Real-time heuristic search algorithms are suitable for situated agents that need to make their decisions in constant time. Since the original work by Korf nearly two decades ago, numerous extensions have been suggested. One of the most…

Artificial Intelligence · Computer Science 2009-12-17 Valeriy K. Bulitko , Vadim Bulitko

We model the time evolution of single win odds in Japanese horse racing as a stochastic process, deriving an Ornstein--Uhlenbeck process by analyzing the probability dynamics of vote shares and the empirical time series of odds movements.…

Physics and Society · Physics 2025-05-22 Tomoya Sugawara , Shintaro Mori

The present paper aims to extend the knight's tour problem for $k$-dimensional grids of the form $\{0,1\}^k$ to other fairy chess leapers. Accordingly, we constructively show the existence of closed tours in $2 \times 2 \times \cdots \times…

General Mathematics · Mathematics 2025-04-03 Gabriele Di Pietro , Marco Ripà

Order Picker Routing is a critical issue in Warehouse Operations Management. Due to the complexity of the problem and the need for quick solutions, suboptimal algorithms are frequently employed in practice. However, Reinforcement Learning…

Machine Learning · Computer Science 2024-02-07 George Dunn , Hadi Charkhgard , Ali Eshragh , Sasan Mahmoudinazlou , Elizabeth Stojanovski

Selection HHs are randomised search methodologies which choose and execute heuristics during the optimisation process from a set of low-level heuristics. A machine learning mechanism is generally used to decide which low-level heuristic…

Neural and Evolutionary Computing · Computer Science 2019-05-16 Andrei Lissovoi , Pietro S. Oliveto , John Alasdair Warwicker

We propose a quantum heuristic algorithm to solve a traveling salesman problem by generalizing Grover search. Sufficient conditions are derived to greatly enhance the probability of finding the tours with extremal costs, reaching almost to…

Quantum Physics · Physics 2013-01-08 Jeongho Bang , Seokwon Yoo , James Lim , Junghee Ryu , Changhyoup Lee , Jinhyoung Lee

Balanced knockout tournaments are ubiquitous in sports competitions and are also used in decision-making and elections. The traditional computational question, that asks to compute a draw (optimal draw) that maximizes the winning…

Computer Science and Game Theory · Computer Science 2016-04-19 Krishnendu Chatterjee , Rasmus Ibsen-Jensen , Josef Tkadlec

The $n$-queens puzzle is to place $n$ mutually non-attacking queens on an $n \times n$ chessboard. We present a simple two stage randomized algorithm to construct such configurations. In the first stage, a random greedy algorithm constructs…

Combinatorics · Mathematics 2021-07-12 Zur Luria , Michael Simkin

A deck of $n$ cards is shuffled by repeatedly moving the top card to one of the bottom $k_n$ positions uniformly at random. We give upper and lower bounds on the total variation mixing time for this shuffle as $k_n$ ranges from a constant…

Probability · Mathematics 2007-05-23 Sharad Goel

This paper considers the problem of regression over distributions, which is becoming increasingly important in machine learning. Existing approaches often ignore the geometry of the probability space or are computationally expensive. To…

Machine Learning · Computer Science 2025-10-31 Maksim Maslov , Alexander Kugaevskikh , Matthew Ivanov

When trying to find approximate solutions for the Traveling Salesman Problem with heuristic optimization algorithms, small moves called Lin-$k$-Opts are often used. In our paper, we provide exact formulas for the numbers of possible tours…

Computational Physics · Physics 2007-05-23 Guenther Stattenberger , Markus Dankesreiter , Florian Baumgartner , Johannes J. Schneider

Gambits are central to human decision-making. Our goal is to provide a theory of Gambits. A Gambit is a combination of psychological and technical factors designed to disrupt predictable play. Chess provides an environment to study gambits…

Theoretical Economics · Economics 2022-04-14 Shiva Maharaj , Nicholas Polson , Christian Turk

A tournament is an orientation of a complete graph. A vertex that can reach every other vertex within two steps is called a \emph{king}. We study the complexity of finding $k$ kings in a tournament graph. We show that the randomized query…

Data Structures and Algorithms · Computer Science 2024-10-15 Amir Abboud , Tomer Grossman , Moni Naor , Tomer Solomon

The game of best choice (also known as the secretary problem) is a model for sequential decision making with a long history and many variations. The classical setup assumes that the sequence of candidate rankings are uniformly distributed.…

Combinatorics · Mathematics 2019-11-06 Brant Jones

Decision making under uncertainty is a key component of many AI settings, and in particular of voting scenarios where strategic agents are trying to reach a joint decision. The common approach to handle uncertainty is by maximizing expected…

Computer Science and Game Theory · Computer Science 2018-11-15 Omer Lev , Reshef Meir , Svetlana Obraztsova , Maria Polukarov

The 2-Opt heuristic is a simple improvement heuristic for the Traveling Salesman Problem. It starts with an arbitrary tour and then repeatedly replaces two edges of the tour by two other edges, as long as this yields a shorter tour. We will…

Data Structures and Algorithms · Computer Science 2021-01-26 Ulrich A. Brodowsky , Stefan Hougardy

We consider a card guessing game with complete feedback. An ordered deck of $n$ cards labeled $1$ up to $n$ is riffle-shuffled exactly one time. Given a value $p\in(0{,}1)\setminus\{\frac12\}$, the riffle shuffle is assumed to be…

Combinatorics · Mathematics 2026-02-13 Markus Kuba

How many shuffles are needed to mix up a deck of cards? This question may be answered in the language of a random walk on the symmetric group, $S_{52}$. This generalises neatly to the study of random walks on finite groups, themselves a…

Probability · Mathematics 2015-04-22 J. P. McCarthy

We revisit an old minor topic in algorithms, the deterministic walk on a finite graph which always moves toward the nearest unvisited vertex until every vertex is visited. There is an elementary connection between this cover time and…

Probability · Mathematics 2021-03-19 David Aldous