Publicaties

Future digital factories are becoming more and more softwarized. This introduces flexibility, but the industry also demands robustness and Quality of Service (QoS) support. While 5G envisions to enable real-time applications with strict performance requirements, IEEE 802.11 networks continue to be a viable option for indoor scenarios. However, IEEE 802.11 networks currently cannot be programmed fine-grained enough to fully support and ensure ...

We present a personalized approach for frequent fitness monitoring in road cycling solely relying on sensor data collected during bike rides and without the need for maximal effort tests. We use competition and training data of three world-class cyclists of Team Jumbo-Visma to construct personalised heart rate models that relate the heart rate during exercise to the pedal power signal. Our model captures the non-trivial dependency between ...

Next-generation communication systems will face new challenges related to efficiently managing the available resources, such as the radio spectrum. DL is one of the optimization approaches to address and solve these challenges. However, there is a gap between research and industry. Most AI models that solve communication problems cannot be implemented in current communication devices due to their high computational capacity requirements. New ...

Combined heat distribution circuits (CHDCs) are increasingly used in apartment buildings. Here only one supply pipe distributes both space heating (SH) and domestic hot water (DHW). Currently, the supply temperature is set to the highest temperature needed by one of the end-users (i.e. 65ºC for DHW), even if low-temperature emitters are used for SH. However, using decentral storage tanks for DHW enable demand-based temperature controls to reduce ...

As manual Management and Orchestration (MANO) of services and resources might delay the execution of MANO operations and negatively impact the performance of 5G and beyond Vehicle-to-Everything (V2X) services, applying AI in MANO to enable automation and intelligence is an imperative. The Network Function Virtualization (NFV), Software Defined Networking (SDN), and Artificial Intelligence (AI), could all together mitigate those challenges, and ...

In current production shop floors, a fleet of production machines and AGVs form a full manufacturing system with a high degree of automation. These current manufacturing systems need to deal with high variability of products and production tasks. Every task, however, requires a proper reconfiguration & control that is often done manually requiring complex settings and long configuration time. With AI techniques the reconfiguration of these ...

Recent work in multi-agent reinforcement learning has investigated inter agent communication which is learned simultaneously with the action policy in order to improve the team reward. In this paper, we investigate independent Q-learning (IQL) without communication and differentiable inter-agent learning (DIAL) with learned communication on an adaptive traffic control system (ATCS). In real world ATCS, it is impossible to present the full state ...

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In this paper, we investigate the current state of the art in Multi- Objective Reinforcement Learning (MORL) benchmarking for problems with discrete state and action spaces. Our investigation finds that there exist a large number of different MORL benchmarks, but there seems to be little standardization among the MORL community. Through a quantative comparison, it becomes clear that many of the MORL benchmarks being used today do not have the ...

By using communication between multiple agents in multi-agent environments, one can reduce the effects of partial observability by combining one agent's observation with that of others in the same dynamic environment. While a lot of successful research has been done towards communication learning in cooperative settings, communication learning in mixed cooperative-competitive settings is also important and brings its own complexities such as the ...