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Mark Drummond

dblp:46/4442 · DBLP profile ↗
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12ranked-venue papers
8as first author
0since 2021 · last 1995
0000-0001-5120-2575ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 11 · 7 first-authorGraphics, computer vision, multimedia, augmented reality and games · 7 · 5 first-authorTheory of computation · 2 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 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.

Artificial intelligence
8 papers
Planning, search and constraint satisfaction · 80% Motion planning and robot control · 11% Knowledge representation and reasoning · 8%
Theoretical computer science
1 paper
Mathematical optimization · 77% Approximation and online algorithms · 23%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 87% Distributed systems · 13%

Topics — the 8 heaviest of 14, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › classical planning
partial-order planning
0.021992
Total Order vs. Partial Order Planning: Factors Influencing Performance · KR 1992
Goal Ordering in Partially Ordered Plans · IJCAI 1989
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
scheduling
0.011994
Just-In-Case Scheduling · AAAI 1994
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
heuristic search
0.011993
Reaction-First Search · IJCAI 1993
Robotics › Motion planning and robot control › motion planning
anytime planning
0.011990
Anytime Synthetic Projection: Maximizing the Probability of Goal Satisfaction · AAAI 1990
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › search control
goal ordering
0.011989
Goal Ordering in Partially Ordered Plans · IJCAI 1989
Embedded and real-time systems › real-time operating systems
real-time kernel
0.011982
PACKRAT - A Real Time Kernel for Distributed Systems · RTSS 1982
Embedded and real-time systems
real-time operating systems
0.011982
PACKRAT - A Real Time Kernel for Distributed Systems · RTSS 1982
Knowledge, reasoning and agents › Knowledge representation and reasoning
action and change
0.011989
Situated Control Rules · KR 1989

Methods — techniques the papers use, named apart from their topics

expected solution quality analysis · 0.0
YearPublicationVenuePosition
1995 Expected Solution Quality
John L. Bresina, Mark Drummond, Keith Swanson
IJCAI2
1994 Just-In-Case Scheduling
Mark Drummond, John L. Bresina, Keith Swanson
AAAI1
1994 Total-Order and Partial-Order Planning: A Comparative Analysis
abstract
For many years, the intuitions underlying partial-order planning were largely taken for granted. Only in the past few years has there been renewed interest in the fundamental principles underlying this paradigm. In this paper, we present a rigorous comparative analysis of partial-order and total-order planning by focusing on two specific planners that can be directly compared. We show that there are some subtle assumptions that underly the wide-spread intuitions regarding the supposed efficiency of partial-order planning. For instance, the superiority ofpartial-order planning can depend critically upon the search strategy and the structure of the search space. Understanding the underlying assumptions is crucial for constructing efficient planners.
Steven Minton, John L. Bresina, Mark Drummond
J. Artif. Intell. Res.3
1993 Reaction-First Search
Mark Drummond, Keith Swanson, John L. Bresina, Richard Levinson
IJCAI1
1992 Total Order vs. Partial Order Planning: Factors Influencing Performance
Steven Minton, Mark Drummond, John L. Bresina, Andrew B. Philips
KR2
1991 Commitment Strategies in Planning: A Comparative Analysis
Steven Minton, John L. Bresina, Mark Drummond
IJCAI3
1990 Anytime Synthetic Projection: Maximizing the Probability of Goal Satisfaction
Mark Drummond, John L. Bresina
AAAI1
1989 Goal Ordering in Partially Ordered Plans
Mark Drummond, Ken Currie
IJCAI1
1989 Situated Control Rules
Mark Drummond
KR1
1988 Exploiting temporal coherence in nonlinear plan construction
abstract
Correct conventional nonlinear planners operate in accordance with Chapman's modal truth criterion (MTC). The MTC characterizes the conditions under which an assertion will be true at a point in a nonlinear plan. However, the MTC is not all one requires in order to build a realistic planning system: it merely sanctions the use of a number of plan modifications in order to achieve each assertion in a developing plan. The number of modifications that can be made is usually very large. To avoid breadth‐first search a planner must have some idea of which plan modification to consider. We describe a domain‐independent search heuristic called temporal coherence, which helps guide the search through the space of partial plans defined by the MTC. Temporal coherence works by suggesting certain orderings of goal achievement as more appealing than others, and thus by finding bindings for plan variables consistent with the planner's overall goals. Our experience with a real nonlinear planner has highlighted the need for such a heuristic. In this paper, we give an example planning problem and use it to illustrate how temporal coherence can speed the search for an acceptable plan. We also prove that if a solution exists in the partial plan search space defined by the MTC, then there exists a path to that solution which is sanctioned by temporal coherence.
Mark Drummond, Ken Currie
Comput. Intell.1
1985 Refining and Extending the Procedural Net
Mark Drummond
IJCAI1
1982 PACKRAT - A Real Time Kernel for Distributed Systems
Mark Drummond, Clare Mcmullen, R. Vasudevan
RTSS1