VLDB 2026 Research / reviewers in the wild / expert
Donald F. Beal
dblp:56/5942 · also Don Beal
· DBLP profile ↗
8ranked-venue papers
5as first author
0since 2021 · last 2001
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 2 first-authorSystems, architecture and hardware · 2 · 1 first-authorDatabases, data management, data science and information retrieval · 2 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-authorTheory of computation · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
Parallel and multicore computing · 67% High-performance computing · 20% Reconfigurable computing and FPGAs · 13% | |
| Artificial intelligence
2 papers |
Reinforcement learning · 63% Video understanding and tracking · 19% Planning, search and constraint satisfaction · 18% |
Topics — the 5 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Reinforcement learning
temporal difference learning |
0.0 | 1 | 1999 | Temporal Coherence and Prediction Decay in TD Learning · IJCAI 1999 |
Parallel and multicore computing › parallel architecture
massively parallel architecture |
0.0 | 1 | 1991 | GPFP: an array processing element for the next generation of massively parallel supercomputer architectures · SC 1991 |
Reconfigurable computing and FPGAs › coarse-grained reconfigurable architecture
processing element array |
0.0 | 1 | 1991 | GPFP: an array processing element for the next generation of massively parallel supercomputer architectures · SC 1991 |
Computer vision › Video understanding and tracking › temporal modeling
temporal consistency |
0.0 | 1 | 1999 | Temporal Coherence and Prediction Decay in TD Learning · IJCAI 1999 |
High-performance computing
supercomputer architecture |
0.0 | 1 | 1991 | GPFP: an array processing element for the next generation of massively parallel supercomputer architectures · SC 1991 |
Methods — techniques the papers use, named apart from their topics
parallelization · 0.0exhaustive search · 0.0temporal difference learning · 0.0array processing · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | Parallel Retrograde Analysis on Different ArchitectureabstractRetrograde analysis is an efficient exhaustive search method. It is a powerful tool that can be used in solving problems where end states have known values but starting states do not. It has been widely used to solve mathematically-precise games such as chess endgames, and is potentially usable in energy-minimization problems. With increasing computing power, both in speed and storage capacity, retrograde analysis will become more and more useful. This paper looks at successful applications to games, the challenges ahead and the modifications that are required to utilize distributed hardware. The power and the usefulness of retrograde analysis are still limited by the computing resources one has access to. Today, the best sequential retrograde algorithms are capable of solving problems with about 10/sup 9/ states in a few hours on a standard personal computer. Bigger problems need more powerful computers, or take much longer to solve, or are simply out of the reach of today's technologies. Introducing parallelism to retrograde analysis is a natural way to attack the bigger problems. There are today three main architectures available for doing parallel retrograde analysis, namely symmetric multiprocessor (SMP) systems, high-speed network-based distributed systems and Internet-based distributed systems. In this paper, we discuss some of the key issues in doing parallel retrograde analysis on these different architectures. Technical challenges are addressed in detail, as well as some examples and proposals. These examples and proposals are drawn from various board games, but the ideas can be applied to other problem domains. Ren Wu, Donald F. Beal |
HPDC | 2 |
| 2001 | Solving Chinese chess endgames by database construction
Ren Wu, Donald F. Beal |
Inf. Sci. | 2 |
| 2001 | Temporal difference learning applied to game playing and the results of application to Shogi
Donald F. Beal, Martin C. Smith |
Theor. Comput. Sci. | 1 |
| 2000 | Temporal Difference Learning for Heuristic Search and Game Playing
Donald F. Beal, Martin C. Smith |
Inf. Sci. | 1 |
| 1999 | Temporal Coherence and Prediction Decay in TD Learning
Donald F. Beal, Martin C. Smith |
IJCAI | 1 |
| 1991 | GPFP: an array processing element for the next generation of massively parallel supercomputer architecturesabstractArticle GPFP: an array processing element for the next generation of massively parallel supercomputer architectures Share on Authors: Don Beal Department of Computer Science, Queen Mary and Westfield College, University of London, London E1 4NS, United Kingdom Department of Computer Science, Queen Mary and Westfield College, University of London, London E1 4NS, United KingdomView Profile , Costas Lambrinoudakis Department of Computer Science, Queen Mary and Westfield College, University of London, London E1 4NS, United Kingdom Department of Computer Science, Queen Mary and Westfield College, University of London, London E1 4NS, United KingdomView Profile Authors Info & Claims Supercomputing '91: Proceedings of the 1991 ACM/IEEE conference on SupercomputingAugust 1991 Pages 348–357https://doi.org/10.1145/125826.126024Online:01 August 1991Publication History 0citation252DownloadsMetricsTotal Citations0Total Downloads252Last 12 Months1Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access Donald F. Beal, Costas Lambrinoudakis |
SC | 1 |
| 1990 | A Generalised Quiescence Search Algorithm
Donald F. Beal |
Artif. Intell. | 1 |
| 1990 | Introduction
Hans J. Berliner, Donald F. Beal |
Artif. Intell. | 2 |