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740 results on '"Hindriks, Koen"'

1. Spectral oversubtraction? An approach for speech enhancement after robot ego speech filtering in semi-real-time

Author

Li, Yue, Hindriks, Koen V., and Kunneman, Florian A.

Subjects
Computer Science - Robotics, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing, 68T50
Abstract

Spectral subtraction, widely used for its simplicity, has been employed to address the Robot Ego Speech Filtering (RESF) problem for detecting speech contents of human interruption from robot's single-channel microphone recordings when it is speaking. However, this approach suffers from oversubtraction in the fundamental frequency range (FFR), leading to degraded speech content recognition. To address this, we propose a Two-Mask Conformer-based Metric Generative Adversarial Network (CMGAN) to enhance the detected speech and improve recognition results. Our model compensates for oversubtracted FFR values with high-frequency information and long-term features and then de-noises the new spectrogram. In addition, we introduce an incremental processing method that allows semi-real-time audio processing with streaming input on a network trained on long fixed-length input. Evaluations of two datasets, including one with unseen noise, demonstrate significant improvements in recognition accuracy and the effectiveness of the proposed two-mask approach and incremental processing, enhancing the robustness of the proposed RESF pipeline in real-world HRI scenarios., Comment: 6 pages, 2 figures, submitted to 2025 IEEE ICASSP

Published
2024

2. 'Give Me an Example Like This': Episodic Active Reinforcement Learning from Demonstrations

Author

Hou, Muhan, Hindriks, Koen, Eiben, A. E., and Baraka, Kim

Subjects
Computer Science - Artificial Intelligence
Abstract

Reinforcement Learning (RL) has achieved great success in sequential decision-making problems, but often at the cost of a large number of agent-environment interactions. To improve sample efficiency, methods like Reinforcement Learning from Expert Demonstrations (RLED) introduce external expert demonstrations to facilitate agent exploration during the learning process. In practice, these demonstrations, which are often collected from human users, are costly and hence often constrained to a limited amount. How to select the best set of human demonstrations that is most beneficial for learning therefore becomes a major concern. This paper presents EARLY (Episodic Active Learning from demonstration querY), an algorithm that enables a learning agent to generate optimized queries of expert demonstrations in a trajectory-based feature space. Based on a trajectory-level estimate of uncertainty in the agent's current policy, EARLY determines the optimized timing and content for feature-based queries. By querying episodic demonstrations as opposed to isolated state-action pairs, EARLY improves the human teaching experience and achieves better learning performance. We validate the effectiveness of our method in three simulated navigation tasks of increasing difficulty. The results show that our method is able to achieve expert-level performance for all three tasks with convergence over 30\% faster than other baseline methods when demonstrations are generated by simulated oracle policies. The results of a follow-up pilot user study (N=18) further validate that our method can still maintain a significantly better convergence in the case of human expert demonstrators while achieving a better user experience in perceived task load and consuming significantly less human time.

Published
2024

3. A Near-Real-Time Processing Ego Speech Filtering Pipeline Designed for Speech Interruption During Human-Robot Interaction

Author

Li, Yue, Kunneman, Florian A., and Hindriks, Koen V.

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

With current state-of-the-art automatic speech recognition (ASR) systems, it is not possible to transcribe overlapping speech audio streams separately. Consequently, when these ASR systems are used as part of a social robot like Pepper for interaction with a human, it is common practice to close the robot's microphone while it is talking itself. This prevents the human users to interrupt the robot, which limits speech-based human-robot interaction. To enable a more natural interaction which allows for such interruptions, we propose an audio processing pipeline for filtering out robot's ego speech using only a single-channel microphone. This pipeline takes advantage of the possibility to feed the robot ego speech signal, generated by a text-to-speech API, as training data into a machine learning model. The proposed pipeline combines a convolutional neural network and spectral subtraction to extract overlapping human speech from the audio recorded by the robot-embedded microphone. When evaluating on a held-out test set, we find that this pipeline outperforms our previous approach to this task, as well as state-of-the-art target speech extraction systems that were retrained on the same dataset. We have also integrated the proposed pipeline into a lightweight robot software development framework to make it available for broader use. As a step towards demonstrating the feasibility of deploying our pipeline, we use this framework to evaluate the effectiveness of the pipeline in a small lab-based feasibility pilot using the social robot Pepper. Our results show that when participants interrupt the robot, the pipeline can extract the participant's speech from one-second streaming audio buffers received by the robot-embedded single-channel microphone, hence in near-real time., Comment: 8 pages,16 figures, Under review by RoMan 2024 conference

Published
2024

4. Quality of Care Perceived by Older Patients and Caregivers in Integrated Care Pathways With Interviewing Assistance From a Social Robot: Noninferiority Randomized Controlled Trial

Author

Boumans, Roel, van Meulen, Fokke, van Aalst, William, Albers, Joyce, Janssen, Marèse, Peters-Kop, Marieke, Huisman - de Waal, Getty, van de Poll, Alexandra, Hindriks, Koen, Neerincx, Mark, and Olde Rikkert, Marcel

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

BackgroundSociety is facing a global shortage of 17 million health care workers, along with increasing health care demands from a growing number of older adults. Social robots are being considered as solutions to part of this problem. ObjectiveOur objective is to evaluate the quality of care perceived by patients and caregivers for an integrated care pathway in an outpatient clinic using a social robot for patient-reported outcome measure (PROM) interviews versus the currently used professional interviews. MethodsA multicenter, two-parallel-group, nonblinded, randomized controlled trial was used to test for noninferiority of the quality of care delivered through robot-assisted care. The randomization was performed using a computer-generated table. The setting consisted of two outpatient clinics, and the study took place from July to December 2019. Of 419 patients who visited the participating outpatient clinics, 110 older patients met the criteria for recruitment. Inclusion criteria were the ability to speak and read Dutch and being assisted by a participating health care professional. Exclusion criteria were serious hearing or vision problems, serious cognitive problems, and paranoia or similar psychiatric problems. The intervention consisted of a social robot conducting a 36-item PROM. As the main outcome measure, the customized Consumer Quality Index (CQI) was used, as reported by patients and caregivers for the outpatient pathway of care. ResultsIn total, 75 intermediately frail older patients were included in the study, randomly assigned to the intervention and control groups, and processed: 36 female (48%) and 39 male (52%); mean age 77.4 years (SD 7.3), range 60-91 years. There was no significant difference in the total patient CQI scores between the patients included in the robot-assisted care pathway (mean 9.27, SD 0.65, n=37) and those in the control group (mean 9.00, SD 0.70, n=38): P=.08, 95% CI –0.04 to 0.58. There was no significant difference in the total CQI scores between caregivers in the intervention group (mean 9.21, SD 0.76, n=30) and those in the control group (mean 9.09, SD 0.60, n=35): P=.47, 95% CI –0.21 to 0.46. No harm or unintended effects occurred. ConclusionsGeriatric patients and their informal caregivers valued robot-assisted and nonrobot-assisted care pathways equally. Trial RegistrationClinicalTrials.gov NCT03857789; https://clinicaltrials.gov/ct2/show/NCT03857789

Published
2020
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5. Single-Channel Robot Ego-Speech Filtering during Human-Robot Interaction

Author

Li, Yue, Hindriks, Koen V, and Kunneman, Florian

Subjects
Computer Science - Robotics, Computer Science - Human-Computer Interaction, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing, I.2.9
Abstract

In this paper, we study how well human speech can automatically be filtered when this overlaps with the voice and fan noise of a social robot, Pepper. We ultimately aim for an HRI scenario where the microphone can remain open when the robot is speaking, enabling a more natural turn-taking scheme where the human can interrupt the robot. To respond appropriately, the robot would need to understand what the interlocutor said in the overlapping part of the speech, which can be accomplished by target speech extraction (TSE). To investigate how well TSE can be accomplished in the context of the popular social robot Pepper, we set out to manufacture a datase composed of a mixture of recorded speech of Pepper itself, its fan noise (which is close to the microphones), and human speech as recorded by the Pepper microphone, in a room with low reverberation and high reverberation. Comparing a signal processing approach, with and without post-filtering, and a convolutional recurrent neural network (CRNN) approach to a state-of-the-art speaker identification-based TSE model, we found that the signal processing approach without post-filtering yielded the best performance in terms of Word Error Rate on the overlapping speech signals with low reverberation, while the CRNN approach is more robust for reverberation. These results show that estimating the human voice in overlapping speech with a robot is possible in real-life application, provided that the room reverberation is low and the human speech has a high volume or high pitch., Comment: Accepted by ACM Technological Advances in Human-Robot Interaction. 9 pages

Published
2024
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6. A Survey on Dialogue Management in Human-Robot Interaction

Author

Reimann, Merle M., Kunneman, Florian A., Oertel, Catharine, and Hindriks, Koen V.

Subjects
Computer Science - Robotics, Computer Science - Human-Computer Interaction
Abstract

As social robots see increasing deployment within the general public, improving the interaction with those robots is essential. Spoken language offers an intuitive interface for the human-robot interaction (HRI), with dialogue management (DM) being a key component in those interactive systems. Yet, to overcome current challenges and manage smooth, informative and engaging interaction a more structural approach to combining HRI and DM is needed. In this systematic review, we analyse the current use of DM in HRI and focus on the type of dialogue manager used, its capabilities, evaluation methods and the challenges specific to DM in HRI. We identify the challenges and current scientific frontier related to the DM approach, interaction domain, robot appearance, physical situatedness and multimodality.

Published
2023

7. Social Robots in the Wild and the Novelty Effect

Author

Reimann, Merle, van de Graaf, Jesper, van Gulik, Nina, van de Sanden, Stephanie, Verhagen, Tibert, Hindriks, Koen, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Ali, Abdulaziz Al, editor, Cabibihan, John-John, editor, Meskin, Nader, editor, Rossi, Silvia, editor, Jiang, Wanyue, editor, He, Hongsheng, editor, and Ge, Shuzhi Sam, editor

Published
2024
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8. Core Elements of Social Interaction for Constructive Human-Robot Interaction

Author

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

Subjects
Computer Science - Human-Computer Interaction
Abstract

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. The two core elements of the social interaction model are engagement and co-regulation. Engagement emphasizes the \textit{qualitative nature} of social interaction and the fact that a user needs to be drawn into the interaction with the robot. Co-regulation emphasizes the interaction process and the fact that a user and a robot need to be acting together. We argue that the quality of social interaction with a robot can be measured in terms of how efficiently engagement and co-regulation are established and maintained during the interaction and how satisfied the user is with the interaction., Comment: Quality of Interaction in Socially Assistive Robots (QISAR) Workshop at International Conference on Social Robotics (ICSR19) - Madrid, Spain, November 26-29, 2019

Published
2021

9. SUPPLE: A Dialogue Management Approach Based on Conversation Patterns

Author

Kunneman, Florian, Hindriks, Koen, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Stoyanchev, Svetlana, editor, Ultes, Stefan, editor, and Li, Haizhou, editor

Published
2022
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11. Integrating Valence and Arousal Within an Agent-Based Model of Emotion Contagion

Author

van Haeringen, Erik, Gerritsen, Charlotte, Hindriks, Koen, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dignum, Frank, editor, Corchado, Juan Manuel, editor, and De La Prieta, Fernando, editor

Published
2021
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13. The 'Why Did You Do That?' Button: Answering Why-Questions for End Users of Robotic Systems

Author

Koeman, Vincent J., Dennis, Louise A., Webster, Matt, Fisher, Michael, Hindriks, Koen, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Dennis, Louise A., editor, Bordini, Rafael H., editor, and Lespérance, Yves, editor

Published
2020
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14. A Study on Automated Receptionists in a Real-World Scenario

Author

Wolter, Ralf, Hindriks, Koen V., Samur, Dalya, Jonker, Catholijn M., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Demazeau, Yves, editor, Holvoet, Tom, editor, Corchado, Juan M., editor, and Costantini, Stefania, editor

Published
2020
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15. Audio-Visual Speech Recognition for Human-Robot Interaction: A Feasibility Study

Author

Goetzee, Sander, Mihhailov, Konstantin, van de Laar, Roel, Baraka, Kim, Hindriks, Koen, Goetzee, Sander, Mihhailov, Konstantin, van de Laar, Roel, Baraka, Kim, and Hindriks, Koen

Abstract

Recent models for Visual Speech Recognition (VSR) have shown remarkable progress over the last few years. They have however been applied mainly to datasets such as Lip Reading Sentences 3 (LRS3), LRS2 or Lombard GRID, but not yet on social robots. As social robots struggle to recognize speech in more challenging acoustic and crowded environments, we believe such models are promising tools for real-time interaction with users. This paper presents a feasibility study focusing on integration of speech recognition (SR) using mixed modalities - audio, visual (lip-reading) and audio-visual - in social robots. To this end, this paper contributes a pipeline to detect an active speaker based on lip movement, post-processing of audio and video footage and inferencing it with the state-of-the-art Auto-AVSR model. In a user study (N=26), we evaluated the feasibility of audio, visual and mixed modality speech recognition on a Pepper robot. We demonstrate the feasibility of using singular and mixed modalities with speech-to-text inference in natural interaction. The results show that it is feasible to deploy such models on social robots in a controlled, noiseless and non-interactive environment. Additionally, the results revealed that informing participants to emphasize their lip movements significantly improved text-to-speech inference results. Our work provides initial insights into the benefits and challenges of using VSR, ASR and AVSR for HRI.

Published
2024

16. Getting Acquainted for a Long-Term Child-Robot Interaction

Author

Ligthart, Mike, Neerincx, Mark. A., Hindriks, Koen V., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Salichs, Miguel A., editor, Ge, Shuzhi Sam, editor, Barakova, Emilia Ivanova, editor, Cabibihan, John-John, editor, Wagner, Alan R., editor, Castro-González, Álvaro, editor, and He, Hongsheng, editor

Published
2019
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17. A Robot Math Tutor that Gives Feedback

Author

Hindriks, Koen V., Liebens, Sander, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Salichs, Miguel A., editor, Ge, Shuzhi Sam, editor, Barakova, Emilia Ivanova, editor, Cabibihan, John-John, editor, Wagner, Alan R., editor, Castro-González, Álvaro, editor, and He, Hongsheng, editor

Published
2019
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18. Designing a Cognitive Agent Connector for Complex Environments: A Case Study with StarCraft

Author

Koeman, Vincent J., Griffioen, Harm J., Plenge, Danny C., Hindriks, Koen V., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Weyns, Danny, editor, Mascardi, Viviana, editor, and Ricci, Alessandro, editor

Published
2019
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25. Back to School - Sustaining Recurring Child-Robot Educational Interactions After a Long Break.

Author

Ligthart, Mike E.U., De Droog, Simone M., Bossema, Marianne, Elloumi, Lamia, de Haas, Mirjam, Smakman, Matthijs H.J., Hindriks, Koen V., and Ben Allouch, Somaya

Subjects
MATHEMATICS education, SOCIALIZATION, INFORMATION sharing, ROBOTICS, LONGITUDINAL method
Abstract

Maintaining the child-robot relationship after a significant break, such as a holiday, is an important step for developing sustainable social robots for education. We ran a four-session user study (n = 113 children) that included a nine-month break between the third and fourth session. During the study, participants practiced math with the help of a social robot math tutor. We found that social personalization is an effective strategy to better sustain the child-robot relationship than the absence of social personalization. To become reacquainted after the long break, the robot summarizes a few pieces of information it had stored about the child. This gives children a feeling of being remembered, which is a key contributor to the effectiveness of social personalization. Enabling the robot to refer to information previously shared by the child is another key contributor to social personalization. Conditional for its effectiveness, however, is that children notice these memory references. Finally, although we found that children's interest in the tutoring content is related to relationship formation, personalizing the topics did not lead to more interest in the content. It seems likely that not all of the memory information that was used to personalize the content was up-to-date or socially relevant. [ABSTRACT FROM AUTHOR]

Published
2024
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26. The Sixth Automated Negotiating Agents Competition (ANAC 2015)

Author

Fujita, Katsuhide, Aydoğan, Reyhan, Baarslag, Tim, Hindriks, Koen, Ito, Takayuki, Jonker, Catholijn, Kacprzyk, Janusz, Series editor, Fujita, Katsuhide, editor, Bai, Quan, editor, Ito, Takayuki, editor, Zhang, Minjie, editor, Ren, Fenghui, editor, Aydoğan, Reyhan, editor, and Hadfi, Rafik, editor

Published
2017
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27. Alternating Offers Protocols for Multilateral Negotiation

Author

Aydoğan, Reyhan, Festen, David, Hindriks, Koen V., Jonker, Catholijn M., Kacprzyk, Janusz, Series editor, Fujita, Katsuhide, editor, Bai, Quan, editor, Ito, Takayuki, editor, Zhang, Minjie, editor, Ren, Fenghui, editor, Aydoğan, Reyhan, editor, and Hadfi, Rafik, editor

Published
2017
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28. Exploring the Ethical Landscape of Robot-Assisted Search and Rescue

Author

Harbers, Maaike, de Greeff, Joachim, Kruijff-Korbayová, Ivana, Neerincx, Mark A., Hindriks, Koen V., Tzafestas, S.G., Series editor, Antsaklis, P., Advisory editor, Gans, N.R., Advisory editor, Tzafestas, C., Advisory editor, Aldinhas Ferreira, Maria Isabel, editor, Silva Sequeira, Joao, editor, Tokhi, Mohammad Osman, editor, E. Kadar, Endre, editor, and Virk, Gurvinder Singh, editor

Published
2017
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29. An Introduction to the Pocket Negotiator: A General Purpose Negotiation Support System

Author

Jonker, Catholijn M., Aydoğan, Reyhan, Baarslag, Tim, Broekens, Joost, Detweiler, Christian A., Hindriks, Koen V., Huldtgren, Alina, Pasman, Wouter, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Criado Pacheco, Natalia, editor, Carrascosa, Carlos, editor, Osman, Nardine, editor, and Julián Inglada, Vicente, editor

Published
2017
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30. Boolean Negotiation Games

Author

Bulling, Nils, Hindriks, Koen V., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Aydoğan, Reyhan, editor, Baarslag, Tim, editor, Gerding, Enrico, editor, Jonker, Catholijn M., editor, Julian, Vicente, editor, and Sanchez-Anguix, Victor, editor

Published
2017
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37. Using Automatic Failure Detection for Cognitive Agents in Eclipse (AAMAS 2016 DEMONSTRATION)

Author

Koeman, Vincent J., Hindriks, Koen V., Jonker, Catholijn M., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Baldoni, Matteo, editor, Müller, Jörg P., editor, Nunes, Ingrid, editor, and Zalila-Wenkstern, Rym, editor

Published
2016
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38. CAAF: A Cognitive Affective Agent Programming Framework

Author

Kaptein, Frank, Broekens, Joost, Hindriks, Koen V., Neerincx, Mark, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Traum, David, editor, Swartout, William, editor, Khooshabeh, Peter, editor, Kopp, Stefan, editor, Scherer, Stefan, editor, and Leuski, Anton, editor

Published
2016
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44. Designing a Knowledge Representation Interface for Cognitive Agents

Author

Bagosi, Timea, de Greeff, Joachim, Hindriks, Koen V., Neerincx, Mark A., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Baldoni, Matteo, editor, Baresi, Luciano, editor, and Dastani, Mehdi, editor

Published
2015
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45. Designing a Source-Level Debugger for Cognitive Agent Programs

Author

Koeman, Vincent J., Hindriks, Koen V., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Chen, Qingliang, editor, Torroni, Paolo, editor, Villata, Serena, editor, Hsu, Jane, editor, and Omicini, Andrea, editor

Published
2015
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46. Performance of Communicating Cognitive Agents in Cooperative Robot Teams

Author

Wei, Changyun, Hindriks, Koen V., Jonker, Catholijn M., Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Duval, Béatrice, editor, van den Herik, Jaap, editor, Loiseau, Stephane, editor, and Filipe, Joaquim, editor

Published
2015
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50. Exploring Heuristic Action Selection in Agent Programming

Author

Hindriks, Koen V., Jonker, Catholijn M., Pasman, Wouter, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Hindriks, Koen V., editor, Pokahr, Alexander, editor, and Sardina, Sebastian, editor

Published
2009
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