Reviews the role of working memory in theories of sentence comprehension, and reviews current theoretical positions in sentence processing. The chapter also identifies several gaps in current research: the relative scarcity of computational models, an excessive focus on average behavior, the absence of properly powered studies, and unclear criteria for identifying model fit. The chapter also summarizes the goals of the book: to provide open source code for facilitating reproducible analyses, to go beyond modelling average effects, and to provide a principled workflow for model evaluation and comparison.

The rise of artificial intelligence is mainly associated with software-based robotic systems such as mobile robots, unmanned aerial vehicles, and increasingly, semi-autonomous cars. However, the large gap between the algorithmic and physical worlds leaves existing systems still far from the vision of intelligent and human-friendly robots capable of interacting with and manipulating our human-centered world. The emerging discipline of machine intelligence (MI), unifying robotics and artificial intelligence, aims for trustworthy, embodiment-aware artificial intelligence that is conscious both of itself and its surroundings, adapting its systems to the interactive body it is controlling. The integration of AI and robotics with control, perception and machine-learning systems is crucial if these truly autonomous intelligent systems are to become a reality in our daily lives. Following a review of the history of machine intelligence dating back to its origins in the twelfth century, this chapter discusses the current state of robotics and AI, reviews key systems and modern research directions, outlines remaining challenges and envisages a future of man and machine that is yet to be built.

This chapter provides an overview of the development of empirical translation studies as a rapidly growing and diversified field of Translation Studies since the 1980s. It examines the evolving identify of empirical translation studies in the last four decades, its changing research aims and priorities, as well as the experimentation with and development of corpus research methodologies which underscore the rapid growth of the field.