Accurate models of mechanical system dynamics are often critical for model‐based control
and reinforcement learning. Fully data‐driven dynamics models promise to ease the process …

The efficient exchange of information is an essential aspect of intelligent collective behavior.
Event-triggered control and estimation achieve some efficiency by replacing continuous data …

Statement of need o80 (pronounced “oh-eighty”) is software for synchronizing and
organizing message exchange between (realtime) processes via simple customized Python …

Much work has been done to develop causal reasoning techniques across a number of
domains, however the utilisation of causality within autonomous systems is still in its infancy …

Any machine targeted for human-level intelligence must be able to autonomously use its
prior experience in novel situations, unforeseen by its designers. Such knowledge transfer …

Mining genuine mechanisms underlying the complex data generation process in real-world
systems is a fundamental step in promoting interpretability of, and thus trust in, data-driven …

While typical validation and verification approaches focus on identifying the associations
between data elements using statistical and machine learning methods, the novel methods …

For any agent to effectively learn how to achieve its goals via interaction with environments,
it must have causal reasoning capabilities. Causal reasoning enables an agent to predict …

Model-based algorithms are deeply rooted in modern control and systems theory. However,
they usually come with a critical assumption-access to an accurate model of the system. In …

Deciding on a model structure is a fundamental problem in machine learning. In this paper
we consider the problem of building a data-based model for dynamical systems from a …