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R. Peter Bonasso

dblp:71/5286 · also Pete Bonasso · DBLP profile ↗
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10ranked-venue papers
5as first author
0since 2021 · last 2014
0000-0002-2824-2517ORCID · corroborated

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

Artificial intelligence and machine learning · 7 · 5 first-authorGraphics, computer vision, multimedia, augmented reality and games · 4 · 3 first-authorDatabases, data management, data science and information retrieval · 3

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
4 papers
Motion planning and robot control · 50% Multi-agent systems · 17% Robot navigation and mapping · 12%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%

Topics — the 6 heaviest of 10, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed systems › distributed coordination
multi-agent systems
0.012003
Demonstration: Liaison Agents for Distributed Space Operations · IJCAI 2003
Robotics › Legged, aerial and field robots › underwater robotics
autonomous underwater vehicle
0.011991
Underwater Experiments Using a Reactive System for Autonomous Vehicles · AAAI 1991
Robotics › Motion planning and robot control › robot control
hierarchical control
0.011991
Integrating Reaction Plans and Layered Competences Through Synchronous Control · IJCAI 1991
Robotics › Motion planning and robot control › robot control architecture
reactive system
0.011991
Underwater Experiments Using a Reactive System for Autonomous Vehicles · AAAI 1991
Robotics › Motion planning and robot control
robot control
0.011991
Integrating Reaction Plans and Layered Competences Through Synchronous Control · IJCAI 1991
Robotics › Motion planning and robot control › multi-robot control
synchronization control
0.011991
Integrating Reaction Plans and Layered Competences Through Synchronous Control · IJCAI 1991

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

agent-based coordination · 0.1reactive system · 0.0reactive control · 0.0
YearPublicationVenuePosition
2014 Reasoner Performance on Ontologies for Operations
Scott Bell, Jim Carciofini, Mark S. Boddy, R. Peter Bonasso
KEOD4
2013 PRONTOE - A Case Study for Developing Ontologies for Operations
abstract
Abstract: In this paper, we describe a set of software tools called the PRIDE ONTOlogy Editor (PRONTOE) and a methodology that allows system operators and domain experts to build and maintain ontologies of their sys-tems with no explicit understanding of the underlying ontology representation. We present two case studies: one using NASA flight controllers, and another using the DARPA Robotic Challenge. 1
Scott Bell, R. Peter Bonasso, Mark S. Boddy, David Kortenkamp, Debra Schreckenghost
KEOD2
2013 PRONTOE: An Ontology Editor for Domain Experts
Scott Bell, R. Peter Bonasso, Mark S. Boddy, David Kortenkamp, Debra Schreckenghost
IC3K2
2003 Demonstration: Liaison Agents for Distributed Space Operations
Debra Schreckenghost, R. Peter Bonasso, David Kortenkamp, Cheryl E. Martin, Tod Milam, Carroll Thronesbery
IJCAI2
2002 Supporting group interaction among humans and autonomous agents
abstract
An important aspect of interaction among groups of humans and software agents is supporting collaboration among these heterogeneous agents while they operate remotely and communicate asynchronously. We are developing an architecture that supports multiple humans interacting with multiple automated control agents in such a manner. We are evaluating this architecture with a group consisting of the crew of a space-based vehicle and the automated software agents controlling the vehicle systems. Such agent interaction is modelled as a loosely co-ordinated group because this model minimizes agent commitment to group goals and constraints while addressing a significant portion of crew and control agent group behaviours. In this paper, we give background on human interaction with space-based automation. We identify related research in multi-agent autonomous architectures and single agent human-computer interaction systems, we describe our architecture design for human-software agent groups and we identify research issues in loosely co-ordinated human-software groups.
Debra Schreckenghost, Cheryl E. Martin, R. Peter Bonasso, David Kortenkamp, Tod Milam, Carroll Thronesbery
Connect. Sci.3
1997 Experiences with an architecture for intelligent, reactive agents
abstract
This paper describes an implementation of the 3T robot architecture which has been under development for the last eight years. The architecture uses three levels of abstraction and description languages which are compatible between levels. The makeup of the architecture helps to coordinate planful activities with real-time behaviours for dealing with dynamic environments. In recent years, other architectures have been created with similar attributes but two features distinguish the 3T architecture: (1) a variety of useful software tools have been created to help implement this architecture on multiple real robots; and (2) this architecture, or parts of it, have been implemented on a variety of very different robot systems using different processors, operating systems, effectors and sensor suites.
R. Peter Bonasso, R. James Firby, Erann Gat, David Kortenkamp, David P. Miller, Marc G. Slack
J. Exp. Theor. Artif. Intell.1
1992 A Reactive Robot System for Find and Fetch Tasks in an Outdoor Environment
R. Peter Bonasso, Hendrik James Antonisse, Marc G. Slack
AAAI1
1992 Using parallel program specifications for reactive control of underwater vehicles
R. Peter Bonasso
Appl. Intell.1
1991 Underwater Experiments Using a Reactive System for Autonomous Vehicles
R. Peter Bonasso
AAAI1
1991 Integrating Reaction Plans and Layered Competences Through Synchronous Control
R. Peter Bonasso
IJCAI1