Demo Data from EDBT 2026 / reviewers in the wild / expert
David G. Mitchell
dblp:m/DavidGMitchell
· DBLP profile ↗
18ranked-venue papers
7as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 16 · 7 first-authorTheory of computation · 8 · 2 first-authorSoftware engineering, systems software and programming languages · 4 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 4 · 2 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.
| Theoretical computer science
5 papers |
Computational complexity · 60% Automated reasoning and model checking · 38% Algorithms and data structures · 2% | |
| Software engineering, system software, and programming languages
1 paper |
Programming languages and type systems · 100% | |
| Artificial intelligence
3 papers |
Knowledge representation and reasoning · 69% Planning, search and constraint satisfaction · 31% |
Topics — the 9 heaviest of 11, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Programming languages and type systems › programming paradigms
declarative programming |
0.1 | 1 | 2009 | Declarative Programming of Search Problems with Built-in Arithmetic · IJCAI 2009 |
Computational complexity
constraint satisfaction |
0.1 | 1 | 2005 | A Framework for Representing and Solving NP Search Problems · AAAI 2005 |
Computational complexity › search problems
NP search problems |
0.1 | 1 | 2005 | A Framework for Representing and Solving NP Search Problems · AAAI 2005 |
Automated reasoning and model checking
satisfiability |
0.0 | 4 | 1996 | Generating Hard Satisfiability Problems · Artif. Intell. 1996 Some Pitfalls for Experimenters with Random SAT · Artif. Intell. 1996 A New Method for Solving Hard Satisfiability Problems · AAAI 1992 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
satisfiability |
0.0 | 1 | 1996 | Generating Hard Satisfiability Problems · Artif. Intell. 1996 |
Automated reasoning and model checking › satisfiability
random satisfiability |
0.0 | 1 | 1996 | Some Pitfalls for Experimenters with Random SAT · Artif. Intell. 1996 |
Computational complexity
phase transition |
0.0 | 1 | 1992 | Hard and Easy Distributions of SAT Problems · AAAI 1992 |
Automated reasoning and model checking › satisfiability
SAT solving |
0.0 | 1 | 1992 | A New Method for Solving Hard Satisfiability Problems · AAAI 1992 |
Algorithms and data structures › analysis of algorithms
experimental algorithmics |
0.0 | 1 | 1996 | Some Pitfalls for Experimenters with Random SAT · Artif. Intell. 1996 |
Methods — techniques the papers use, named apart from their topics
local search · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Propagators and Solvers for the Algebra of Modular SystemsabstractSolving complex problems can involve non-trivial combinations of distinct knowledge bases and problem solvers. The Algebra of Modular Systems is a knowledge representation framework that provides a method for formally specifying such systems in purely semantic terms. Many practical systems based on expressive formalisms solve the model expansion task. In this paper, we con- struct a solver for the model expansion task for a complex modular system from an expression in the algebra and black-box propagators or solvers for the primitive modules. To this end, we define a general notion of propagators equipped with an explanation mechanism, an extension of the algebra to propagators, and a lazy conflict-driven learning algorithm. The result is a framework for seamlessly combining solving technology from different domains to produce a solver for a combined system. Bart Bogaerts 0001, Eugenia Ternovska, David G. Mitchell |
LPAR | 3 |
| 2015 | Clause-Learning for Modular Systems
David G. Mitchell, Eugenia Ternovska |
LPNMR | 1 |
| 2013 | Problem Solving with the Enfragmo System
Amir Aavani, Eugenia Ternovska, David G. Mitchell |
Theory Pract. Log. Program. | 3 |
| 2012 | Enfragmo: A System for Modelling and Solving Search Problems with Logic
Amir Aavani, Xiongnan (Newman) Wu, Shahab Tasharrofi, Eugenia Ternovska, David G. Mitchell |
LPAR | 5 |
| 2009 | Declarative Programming of Search Problems with Built-in Arithmetic
Eugenia Ternovska, David G. Mitchell |
IJCAI | 2 |
| 2007 | Faster Phylogenetic Inference with MXG
David G. Mitchell, Faraz Hach, Raheleh Mohebali |
LPAR | 1 |
| 2007 | Minimum 2CNF Resolution Refutations in Polynomial Time
Joshua Buresh-Oppenheim, David G. Mitchell |
SAT | 2 |
| 2006 | Constructing Camin-Sokal Phylogenies Via Answer Set Programming
Jonathan Kavanagh, David G. Mitchell, Eugenia Ternovska, Ján Manuch, Xiaohong Zhao, Arvind Gupta |
LPAR | 2 |
| 2006 | Minimum Witnesses for Unsatisfiable 2CNFs
Joshua Buresh-Oppenheim, David G. Mitchell |
SAT | 2 |
| 2005 | A Framework for Representing and Solving NP Search Problems
David G. Mitchell, Eugenia Ternovska |
AAAI | 1 |
| 2005 | 2-Way vs. d-Way Branching for CSP
Joey Hwang, David G. Mitchell |
CP | 2 |
| 2005 | The resolution complexity of random graph k-colorability
Paul Beame, Joseph C. Culberson, David G. Mitchell, Cristopher Moore |
Discret. Appl. Math. | 3 |
| 2003 | Resolution and Constraint Satisfaction
David G. Mitchell |
CP | 1 |
| 2002 | Resolution Complexity of Random Constraints
David G. Mitchell |
CP | 1 |
| 1996 | Some Pitfalls for Experimenters with Random SAT
David G. Mitchell, Hector J. Levesque |
Artif. Intell. | 1 |
| 1996 | Generating Hard Satisfiability Problems
Bart Selman, David G. Mitchell, Hector J. Levesque |
Artif. Intell. | 2 |
| 1992 | Hard and Easy Distributions of SAT Problems
David G. Mitchell, Bart Selman, Hector J. Levesque |
AAAI | 1 |
| 1992 | A New Method for Solving Hard Satisfiability Problems
Bart Selman, Hector J. Levesque, David G. Mitchell |
AAAI | 3 |