The key concepts that have driven my curiosity in research are: neural networks, self-organization, reinforcement learning, language acquisition, meaning representation, grounded cognition, cognitive robotics, causality, and others.
- Lexicon acquisition: Some time ago, I did work in the field of early lexical acquisition using self-organized networks. The focus was on unsupervised approach that accounts for several developmental phenomena observed in young children.
- Connectionist systematicity: The issue of (syntactic and semantic) systematicity is a continuing challenge for connectionist models that have the ambition to be a plausible account of human cognition. In our work, we focused on syntactic systematicity, tested in a new neural network model (RecSOMsard), as well as the Recursive Auto-Associative Memory (RAAM).
- Computational analysis of neural network model properties - such as recurrent self-organizing maps or echo-state networks. In RecSOMs we focused on the learned representations, in ESNs we focused on maximizing the memory capacity.
- Causality in mind-body relationship: I have for long been fascinated by the "old" problem of the relation between the material body and immaterial mind. On of the tricky questions in this context is the problem of mental causation. I wrote some papers about it that reflect my view about the role of the mental in the physical world, given the physical closure assumption.
- Cognitive robotics: We use the simulated iCub robot in the effort to model the acquisition of various early cognitive skills, such as visuomotor coordination and object-directed actions.