Epistemic defenses against scientific and empirical adversarial AI attacks

In this paper, we introduce “scientific and empirical adversarial AI attacks” (SEA AI attacks) as umbrella term for not yet prevalent but technically feasible deliberate malicious acts of specifically crafting AI-generated samples to achieve an epistemic distortion in (applied) science or engineering contexts. In view of possible socio-psycho...

Orthogonality-based disentanglement of responsibilities for ethical intelligent systems

Hybrid Strategies Towards Safe “Self-Aware” Superintelligent Systems

Against the backdrop of increasing progresses in AI research paired with a rise of AI applications in decision-making processes, security-critical domains as well as in ethically relevant frames, a large-scale debate on possible safety measures encompassing corresponding long-term and short-term issues has emerged across different disciplines....

Telling autonomous systems what to do

Recent progress in Artificial Intelligence, sensing and network technology, robotics, and (cloud) computing has enabled the development of intelligent autonomous machine systems. Telling such autonomous systems "what to do" in a responsible way, is a non-trivial task. For intelligent autonomous machines to function in human society and...

Improvement of Network Performance by In-Vehicle Routing Using Floating Car Data

This paper describes a study which gives insight into the size of improvement that is possible with individual in-car routing advice based on the actual traffic situation derived from floating car data (FCD). It also gives an idea about the required penetration rate of floating car data needed to achieve a certain degree of improvement. The...

Designing on-demand education for simultaneous development of domain-specific and self-directed learning skills

On-demand education enables individual learners to choose their learning pathways according to their own learning needs. They must use self-directed learning (SDL) skills involving self-assessment and task selection to determine appropriate pathways for learning. Learners who lack these skills must develop them because SDL skills are...

The effect of inaccurate traffic data for ramp metering: Comparing loop detectors and cameras using information utility

This paper introduces a topic which is of growing interest in the traffic control and management community, namely the relation between traffic data quality and the efficiency of traffic management. After some explanatory background and state of the art, it will become clear that no standard approach is available for traffic engineers to...

Efficient abstraction selection in reinforcement learning

This paper introduces a novel approach for abstraction selection in reinforcement learning problems modelled as factored Markov decision processes (MDPs), for which a state is described via a set of state components. In abstraction selection, an agent must choose an abstraction from a set of candidate abstractions, each build up from a different...

Switching between Representations in Reinforcement Learning

This chapter presents and evaluates an online representation selection method for factored Markov decision processes (MDPs). The method addresses a special case of the feature selection problem that only considers certain subsets of features, which we call candidate representations. A motivation for the method is that it can potentially deal...

An improved method for creating shared belief in communication constrained sensor networks

Networked systems that gather sensor data in order to react to phenomena in their surroundings are faced with a growing need for adaptive behavior to operate in dynamically changing environments. In designing a networked system the data processing chain can be decomposed into functional components. These functional components interact by...

Radon transforms and time-frequency representations for ISAR motion compensation and imaging

The use of the Radon transform and the Wigner-Radon power spectrum for ISAR motion compensation is described. It is shown that the local Radon power spectrum is closely related to the Cohen's class of quadratic time-frequency representations in a similar way as the Radon and Fourier transform are related. The peak of the local Radon transform is...