Mark H. M. Winands
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View article: Variational Quantum Algorithms for Particle Track Reconstruction
Variational Quantum Algorithms for Particle Track Reconstruction Open
Quantum Computing is a rapidly developing field with the potential to tackle the increasing computational challenges faced in high-energy physics. In this work, we explore the potential and limitations of variational quantum algorithms in …
View article: Automating the static and seismic design of 2-D multistorey reinforced concrete structures by using Monte Carlo Tree Search and Genetic Algorithm
Automating the static and seismic design of 2-D multistorey reinforced concrete structures by using Monte Carlo Tree Search and Genetic Algorithm Open
This research is based on the idea that certain cognitive-intensive tasks typically carried out by structural engineers—such as choosing how to effectively arrange a building’s structure—can be successfully automated. In this article we in…
View article: Generalized Proof-Number Monte-Carlo Tree Search
Generalized Proof-Number Monte-Carlo Tree Search Open
This paper presents Generalized Proof-Number Monte-Carlo Tree Search: a generalization of recently proposed combinations of Proof-Number Search (PNS) with Monte-Carlo Tree Search (MCTS), which use (dis)proof numbers to bias UCB1-based Sele…
View article: A Study on Stabilizer Rényi Entropy Estimation using Machine Learning
A Study on Stabilizer Rényi Entropy Estimation using Machine Learning Open
Nonstabilizerness is a fundamental resource for quantum advantage, as it quantifies the extent to which a quantum state diverges from those states that can be efficiently simulated on a classical computer, the stabilizer states. The stabil…
View article: Towards Explaining Monte-Carlo Tree Search by Using Its Enhancements
Towards Explaining Monte-Carlo Tree Search by Using Its Enhancements Open
Typically, research on Explainable Artificial Intelligence (XAI) focuses on black-box models within the context of a general policy in a known, specific domain. This paper advocates for the need for knowledge-agnostic explainability applie…
View article: Generalized Proof-Number Monte-Carlo Tree Search
Generalized Proof-Number Monte-Carlo Tree Search Open
This paper presents Generalized Proof-Number Monte-Carlo Tree Search: a generalization of recently proposed combinations of Proof-Number Search (PNS) with Monte-Carlo Tree Search (MCTS), which use (dis)proof numbers to bias UCB1-based Sele…
View article: Quantum Circuit Design using a Progressive Widening Enhanced Monte Carlo Tree Search
Quantum Circuit Design using a Progressive Widening Enhanced Monte Carlo Tree Search Open
The performance of Variational Quantum Algorithms (VQAs) strongly depends on the choice of the parameterized quantum circuit to optimize. One of the biggest challenges in VQAs is designing quantum circuits tailored to the particular proble…
View article: Conformal multistep-ahead multivariate time-series forecasting
Conformal multistep-ahead multivariate time-series forecasting Open
Time-series forecasts underpin decision-making processes in a wide range of application domains. Recently it has been shown that these processes can be strengthened by conformal prediction, a framework that allows adding prediction interva…
View article: Quantum Circuit Design using a Progressive Widening Enhanced Monte Carlo Tree Search
Quantum Circuit Design using a Progressive Widening Enhanced Monte Carlo Tree Search Open
The performance of Variational Quantum Algorithms (VQAs) strongly depends on the choice of the parameterized quantum circuit to optimize. One of the biggest challenges in VQAs is designing quantum circuits tailored to the particular proble…
View article: TrackHHL: A Quantum Computing Algorithm for Track Reconstruction at the LHCb
TrackHHL: A Quantum Computing Algorithm for Track Reconstruction at the LHCb Open
In the future high-luminosity LHC era, high-energy physics experiments face unprecedented computational challenges for event reconstruction. Employing the LHCb vertex locator as a case study we investigate a novel approach for charged part…
View article: A Research Agenda for Usability and Generalisation in Reinforcement Learning
A Research Agenda for Usability and Generalisation in Reinforcement Learning Open
It is common practice in reinforcement learning (RL) research to train and deploy agents in bespoke simulators, typically implemented by engineers directly in general-purpose programming languages or hardware acceleration frameworks such a…
View article: Anytime Sequential Halving in Monte-Carlo Tree Search
Anytime Sequential Halving in Monte-Carlo Tree Search Open
Monte-Carlo Tree Search (MCTS) typically uses multi-armed bandit (MAB) strategies designed to minimize cumulative regret, such as UCB1, as its selection strategy. However, in the root node of the search tree, it is more sensible to minimiz…
View article: Editorial: New horizons
Editorial: New horizons Open
View article: Towards a Characterisation of Monte-Carlo Tree Search Performance in Different Games
Towards a Characterisation of Monte-Carlo Tree Search Performance in Different Games Open
Many enhancements to Monte-Carlo Tree Search (MCTS) have been proposed over almost two decades of general game playing and other artificial intelligence research. However, our ability to characterise and understand which variants work well…
View article: Ancestor-Based α-β Bounds for Monte-Carlo Tree Search
Ancestor-Based α-β Bounds for Monte-Carlo Tree Search Open
Upper Confidence bounds applied to Trees (UCT) is the default selection policy in Monte-Carlo Tree Search (MCTS), yet it overlooks the strategic use of ancestral node information. Consequently, UCT approaches each decision level as an inde…
View article: Enhancements for Real-Time Monte-Carlo Tree Search in General Video Game Playing
Enhancements for Real-Time Monte-Carlo Tree Search in General Video Game Playing Open
General Video Game Playing (GVGP) is a field of Artificial Intelligence where agents play a variety of real-time video games that are unknown in advance. This limits the use of domain-specific heuristics. Monte-Carlo Tree Search (MCTS) is …
View article: Towards a Characterisation of Monte-Carlo Tree Search Performance in Different Games
Towards a Characterisation of Monte-Carlo Tree Search Performance in Different Games Open
Many enhancements to Monte-Carlo Tree Search (MCTS) have been proposed over almost two decades of general game playing and other artificial intelligence research. However, our ability to characterise and understand which variants work well…
View article: Editorial: Many quests
Editorial: Many quests Open
In Computer Games research, we have seen a couple of quests over the years.The most famous one was the question whether a chess engine could defeat the human world-champion.This quest really started when in 1956 the first computer chess ga…
View article: Proof Number-Based Monte Carlo Tree Search
Proof Number-Based Monte Carlo Tree Search Open
This paper proposes a new game-search algorithm, PN-MCTS, which combines Monte-Carlo Tree Search (MCTS) and Proof-Number Search (PNS). These two algorithms have been successfully applied for decision making in a range of domains. We define…
View article: Editorial: Looking back, looking forward
Editorial: Looking back, looking forward Open
report om the results of the 32 events.It is followed by a report of Quentin Cohen-Solal and Tristan Cazenave describing their engine ATHÉNAN, which entered 21 events and earned 21 medals, including 16 times
View article: Scheduling Single AGV in Blocking Flow-Shop with Identical Jobs
Scheduling Single AGV in Blocking Flow-Shop with Identical Jobs Open
We consider a flow-shop with m stations (machines) and n identical jobs that need to be processed on each station. The processing time of every job on station i is pi. After a job is processed on a station i, it needs to be tran…
View article: Monte-Carlo Tree Search
Monte-Carlo Tree Search Open
View article: Editorial: Rankings and ratings
Editorial: Rankings and ratings Open
International audience
View article: Explainable Search: An Exploratory Study in SameGame
Explainable Search: An Exploratory Study in SameGame Open
The field of Explainable Artificial Intelligence has gained popularity in recent years, due to the need for users to understand AI-made decisions, in order to increase their trust in the AI system. However, not much work has been performed…
View article: Towards Explainable Linguistic Summaries
Towards Explainable Linguistic Summaries Open
As more AI solutions are implemented in every aspect of our lives, the need for Explainable Artificial Intelligence (XAI) rises. Explanations can have different forms, such as a number (or an equation), a figure, or a text. This paper inve…
View article: Proof Number Based Monte-Carlo Tree Search
Proof Number Based Monte-Carlo Tree Search Open
This paper proposes a new game-search algorithm, PN-MCTS, which combines Monte-Carlo Tree Search (MCTS) and Proof-Number Search (PNS). These two algorithms have been successfully applied for decision making in a range of domains. We define…
View article: Monte-Carlo Tree-Search for Leveraging Performance of Blackbox Job-Shop Scheduling Heuristics
Monte-Carlo Tree-Search for Leveraging Performance of Blackbox Job-Shop Scheduling Heuristics Open
In manufacturing, the production is often done on out-of-the-shelf manufacturing lines, whose underlying scheduling heuristics are not known due to the intellectual property. We consider such a setting with a black-box job-shop system and …
View article: Combining Monte-Carlo Tree Search with Proof-Number Search
Combining Monte-Carlo Tree Search with Proof-Number Search Open
Proof-Number Search (PNS) and Monte-Carlo Tree Search (MCTS) have been successfully applied for decision making in a range of games. This paper proposes a new approach called PN-MCTS that combines these two tree-search methods by incorpora…
View article: Split Moves for Monte-Carlo Tree Search
Split Moves for Monte-Carlo Tree Search Open
In many games, moves consist of several decisions made by the player. These decisions can be viewed as separate moves, which is already a common practice in multi-action games for efficiency reasons. Such division of a player move into a s…
View article: Combining Monte-Carlo Tree Search with Proof-Number Search
Combining Monte-Carlo Tree Search with Proof-Number Search Open
Proof-Number Search (PNS) and Monte-Carlo Tree Search (MCTS) have been successfully applied for decision making in a range of games. This paper proposes a new approach called PN-MCTS that combines these two tree-search methods by incorpora…