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Trust me! I am a robot: an affective computational account of scaffolding in robot-robot interaction
(IEEE, 2021-08-08)
Forming trust in a biological or artificial interaction partner that provides reliable strategies and employing the learned strategies to scaffold another agent are critical problems that are often addressed separately in ...
Effect regulated projection of robot’s action space for production and prediction of manipulation primitives through learning progress and predictability based exploration
(IEEE, 2021-06)
In this study, we propose an effective action parameter exploration mechanism that enables efficient discovery of robot actions through interacting with objects in a simulated table-top environment. For this, the robot ...
Artificial intelligence techniques for conflict resolution
(Springer, 2021-08)
Conflict resolution is essential to obtain cooperation in many scenarios such as politics and business, as well as our day to day life. The importance of conflict resolution has driven research in many fields like anthropology, ...
Data-driven bandwidth prediction models and automated model selection for low latency
(IEEE, 2021)
Today's HTTP adaptive streaming solutions use a variety of algorithms to measure the available network bandwidth and predict its future values. Bandwidth prediction, which is already a difficult task, must be more accurate ...
EXPECTATION: Personalized explainable artificial intelligence for decentralized agents with heterogeneous knowledge
(Springer, 2021)
Explainable AI (XAI) has emerged in recent years as a set of techniques and methodologies to interpret and explain machine learning (ML) predictors. To date, many initiatives have been proposed. Nevertheless, current ...
Can social agents efficiently perform in automated negotiation?
(MDPI, 2021-07)
In the last few years, we witnessed a growing body of literature about automated negotiation. Mainly, negotiating agents are either purely self-driven by maximizing their utility function or by assuming a cooperative stance ...
Inferring cost functions using reward parameter search and policy gradient reinforcement learning
(IEEE, 2021)
This study focuses on inferring cost functions of obtained movement data using reward parameter search and policy gradient based Reinforcement Learning (RL). The behavior data for this task is obtained through a series of ...
VisDrone-MOT2021: The vision meets drone multiple object tracking challenge results
(IEEE, 2021)
Vision Meets Drone: Multiple Object Tracking (VisDrone-MOT2021) challenge - the forth annual activity organized by the VisDrone team - focuses on benchmarking UAV MOT algorithms in realistic challenging environments. It ...
Do not predict – Recompute! How value recomputation can truly boost the performance of invisible speculation
(IEEE, 2021)
Recent architectural approaches that address speculative side-channel attacks aim to prevent software from exposing the microarchitectural state changes of transient execution. The Delay-on-Miss technique is one such ...
Guest editorial special issue on continual unsupervised sensorimotor learning
(IEEE, 2021-06)
The pursuit of higher levels of autonomy and versatility in robotics is arguably led by two main factors. First, as we push robots out of the labs and production lines, it becomes increasingly challenging to design for all ...
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