activity
20172026
most citedContrastive Explanations for Reinforcement Learning in terms of Expected Consequences

65 citations · 109 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CL2026

Dialogue Summarization with Emotion Dynamics Using Topic- and Participant-Centric Decomposition

Linyun Xiang, Mark Neerincx, Stephanie Tan

Existing text summarization research has focused much on monologic information (e.g., newspaper articles, reports) without accounting for the interaction between speakers or author…

cs.CL2023

Modelling prospective memory and resilient situated communications via Wizard of Oz

Yanzhe Li, Frank Broz, Mark Neerincx

This abstract presents a scenario for human-robot action in a home setting involving an older adult and a robot. The scenario is designed to explore the envisioned modelling of mem…

cs.HC2023★ 6 cited

Designing for Meaningful Human Control in Military Human-Machine Teams

Jurriaan van Diggelen, Karel van den Bosch, Mark Neerincx +1

We propose methods for analysis, design, and evaluation of Meaningful Human Control (MHC) for defense technologies from the perspective of military human-machine teaming (HMT). Our…

cs.AI2023★ 3 cited

Persuading to Prepare for Quitting Smoking with a Virtual Coach: Using States and User Characteristics to Predict Behavior

Nele Albers, Mark A. Neerincx, Willem-Paul Brinkman

Despite their prevalence in eHealth applications for behavior change, persuasive messages tend to have small effects on behavior. Conditions or states (e.g., confidence, knowledge,…

cs.AI2022★ 3 cited

A Machine with Short-Term, Episodic, and Semantic Memory Systems

Taewoon Kim, Michael Cochez, Vincent François-Lavet +2

Inspired by the cognitive science theory of the explicit human memory systems, we have modeled an agent with short-term, episodic, and semantic memory systems, each of which is mod…

cs.HC2022★ 2 cited

Exploring Effectiveness of Explanations for Appropriate Trust: Lessons from Cognitive Psychology

Ruben S. Verhagen, Siddharth Mehrotra, Mark A. Neerincx +2

The rapid development of Artificial Intelligence (AI) requires developers and designers of AI systems to focus on the collaboration between humans and machines. AI explanations of…

cs.AI2022★ 1 cited

A Machine With Human-Like Memory Systems

Taewoon Kim, Michael Cochez, Vincent Francois-Lavet +2

Inspired by the cognitive science theory, we explicitly model an agent with both semantic and episodic memory systems, and show that it is better than having just one of the two me…

cs.HC2021★ 2 cited

Core Elements of Social Interaction for Constructive Human-Robot Interaction

Mike E. U. Ligthart, Mark A. Neerincx, Koen V. Hindriks

We present a discovery-based, first version, explicit model of social interaction that provides a basis for measuring the quality of interaction of a human user with a social robot…

cs.HC2020★ 1 cited

A Blast From the Past: Personalizing Predictions of Video-Induced Emotions using Personal Memories as Context

Bernd Dudzik, Joost Broekens, Mark Neerincx +1

A key challenge in the accurate prediction of viewers' emotional responses to video stimuli in real-world applications is accounting for person- and situation-specific variation. A…

cs.RO2020★ 6 cited

Robotic Self-Assessment of Competence

Gertjan J. Burghouts, Albert Huizing, Mark A. Neerincx

In robotics, one of the main challenges is that the on-board Artificial Intelligence (AI) must deal with different or unexpected environments. Such AI agents may be incompetent the…

cs.LG2018★ 65 cited

Contrastive Explanations for Reinforcement Learning in terms of Expected Consequences

Jasper van der Waa, Jurriaan van Diggelen, Karel van den Bosch +1

Machine Learning models become increasingly proficient in complex tasks. However, even for experts in the field, it can be difficult to understand what the model learned. This hamp…

stat.ML2018★ 20 cited

Contrastive Explanations with Local Foil Trees

Jasper van der Waa, Marcel Robeer, Jurriaan van Diggelen +2

Recent advances in interpretable Machine Learning (iML) and eXplainable AI (XAI) construct explanations based on the importance of features in classification tasks. However, in a h…

cs.RO2017

A New UGV Teleoperation Interface for Improved Awareness of Network Connectivity and Physical Surroundings

Ramviyas Parasuraman, Sergio Caccamo, Fredrik Båberg +2

A reliable wireless connection between the operator and the teleoperated Unmanned Ground Vehicle (UGV) is critical in many Urban Search and Rescue (USAR) missions. Unfortunately, a…