Rianne van Lambalgen

dblp:70/5268 · DBLP profile ↗
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8ranked-venue papers
0as first author
0since 2021 · last 2013
0000-0001-5266-8588ORCID · verified

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

Artificial intelligence and machine learning · 8Graphics, computer vision, multimedia, augmented reality and games · 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
1 paper
Multi-agent systems · 70% Knowledge representation and reasoning · 30%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Multi-agent systems
agent modeling
0.112011
Modeling Situation Awareness in Human-Like Agents Using Mental Models · IJCAI 2011
Knowledge, reasoning and agents › Multi-agent systems
context awareness
0.112011
Modeling Situation Awareness in Human-Like Agents Using Mental Models · IJCAI 2011
Knowledge, reasoning and agents › Knowledge representation and reasoning › cognitive modeling
mental models
0.112011
Modeling Situation Awareness in Human-Like Agents Using Mental Models · IJCAI 2011
Knowledge, reasoning and agents › Multi-agent systems
multi-agent decision making
0.012011
Modeling Situation Awareness in Human-Like Agents Using Mental Models · IJCAI 2011

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

simulation · 0.1mental model specification · 0.1
YearPublicationVenuePosition
2013 An agent model for analysis of human performance quality
abstract
A human's performance in a complex task is highly dependent on the demands of the task, in the sense that highly demanding situations will often cause a degradation of performance. To maintain performance quality usually extra effort has to be contri
Michel C. A. Klein, Rianne van Lambalgen, Jan Treur
Web Intell. Agent Syst.2
2012 An Integrated Agent Model for Attention and Functional State
Tibor Bosse, Rianne van Lambalgen, Peter-Paul van Maanen, Jan Treur
IEA/AIE2
2012 A system to support attention allocation: Development and application
abstract
This paper discusses and evaluates an agent model that is able to manipulate the visual attention of a human, in order to support naval crew. The agent model consists of four sub-models, including a model to reason about a subject's attention. The mo
Tibor Bosse, Rianne van Lambalgen, Peter-Paul van Maanen, Jan Treur
Web Intell. Agent Syst.2
2011 Design of an Optimal Automation System: Finding a Balance between a Human's Task Engagement and Exhaustion
Michel C. A. Klein, Rianne van Lambalgen
IEA/AIE (2)2
2011 Modeling Situation Awareness in Human-Like Agents Using Mental Models
abstract
In order for agents to be able to act intelligently in an environment, a first necessary step is to become aware of the current situation in the environment. Forming such awareness is not a trivial matter. Appropriate observations should be selected by the agent, and the observation results should be interpreted and combined into one coherent picture. Humans use dedicated mental models which represent the relationships between various observations and the formation of beliefs about the environment, which then again direct the further observations to be performed. In this paper, a generic agent model for situation awareness is proposed that is able to take a mental model as input, and utilize this model to create a picture of the current situation. In order to show the suitability of the approach, it has been applied within the domain of F-16 fighter pilot training for which a dedicated mental model has been specified, and simulations experiments have been conducted. 1
Mark Hoogendoorn, Rianne van Lambalgen, Jan Treur
IJCAI2
2011 Learning Belief Connections in a Model for Situation Awareness
Maria L. Gini, Mark Hoogendoorn, Rianne van Lambalgen
PRIMA3
2011 An Integrated Agent Model Addressing Situation Awareness and Functional State in Decision Making
Mark Hoogendoorn, Rianne van Lambalgen, Jan Treur
PRIMA2
2009 Adaptation and Validation of an Agent Model of Functional State and Performance for Individuals
Fiemke Griffioen-Both, Mark Hoogendoorn, S. Waqar Jaffry, Rianne van Lambalgen, Rogier Oorburg, Alexei Sharpanskykh, Jan Treur, Michael de Vos
PRIMA4