The Gumbel-max trick is a method to draw a sample from a categorical distribution, given by
its unnormalized (log-) probabilities. Over the past years, the machine learning community …

Creating autonomous robots that can actively explore the environment, acquire knowledge
and learn skills continuously is the ultimate achievement envisioned in cognitive and …

Abstract We present ALFRED (Action Learning From Realistic Environments and Directives),
a benchmark for learning a mapping from natural language instructions and egocentric …

Given a simple request like Put a washed apple in the kitchen fridge, humans can reason in
purely abstract terms by imagining action sequences and scoring their likelihood of success …

Neuro-Symbolic Artificial Intelligence–the combination of symbolic methods with methods
that are based on artificial neural networks–has a long-standing history. In this article, we …

Planning for robotic manipulation requires reasoning about the changes a robot can affect
on objects. When such interactions can be modelled analytically, as in domains with rigid …

Knowledge graphs (KGs) have rapidly emerged as an important area in AI over the last ten
years. Building on a storied tradition of graphs in the AI community, a KG may be simply …

Machine learning has long since become a keystone technology, accelerating science and
applications in a broad range of domains. Consequently, the notion of applying learning …

We present the first approach capable of learning domain-independent planning heuristics
entirely from scratch. The heuristics we learn map the hypergraph representation of the …

Abstract Symbolic Systems in Artificial Intelligence which are based on formal logic and
deductive reasoning are fundamentally different from Artificial Intelligence systems based on …