Are you looking for a PhD position in the burgeoning field of neurosymbolic artificial intelligence at a thriving interdisciplinary institute in Amsterdam? Join us in the research unit of Natural Language Processing at the Institute for Logic, Language and Computation (ILLC), a home to a thriving community of scholars, including philosophers, logicians, mathematicians, computer scientists, linguists, musicologists, and cognitive scientists, who share a fascination with the interdisciplinary study of information.

Are you looking for a postdoc position at the intersection of logic, philosophy and semantics? Would you like to be part of a research team developing new foundations for intensional notions such as property, content, proof, possibility and necessity? If so, come and join the GOOD INTENSIONS project!

Are you looking for a postdoc position at the intersection of logic, philosophy and mathematics? Would you like to be part of a research team developing new foundations for intensional notions such as property, content, proof, possibility and necessity? If so, come and join the GOOD INTENSIONS project!

Are you looking for a PhD position at the intersection of logic, philosophy and semantics? Would you like to be part of a research team developing new foundations for intensional notions such as property, content, proof, possibility and necessity? If so, come and join the GOOD INTENSIONS project!

Arie Soeteman investigates how artificial intelligence can reason in a way that resembles how humans think, according to the laws of logic. Using mathematical proofs and by having AI systems solve puzzles, he demonstrates how self-learning computer systems arrive at conclusions. The goal is to develop AI models that we can understand and trust.

We are pleased to announce that Martha Lewis has been awarded a a NIAS Lorentz Theme Group - Fellowship, to work on what representations AI models need in order to reason analogically.

The Hotelling-Downs model studies strategic positioning of candidates along an ideological line where voters choose the nearest candidate. While equilibrium structure has been widely analyzed, little is known about the computational complexity of finding equilibria. We provide algorithmic results for computing equilibria in both discrete and continuous variants of the model. For the continuous case, we prove a structural result showing that whenever an equilibrium exists, one also exists with rational positions of bounded complexity, enabling discretization via a notion we call reflection barriers. Using dynamic programming, we show: (i) equilibrium existence is decidable in polynomial time for discrete candidate locations; (ii) in the continuous-candidate and discrete-voter setting, equilibria can be computed in pseudo-polynomial time; and (iii) in the fully continuous setting, an ϵ-equilibrium can be computed in time polynomial in 1/ϵ. This is joint work with Umang Bhaskar.

For more information on the Computational Social Choice Seminar, please consult https://staff.science.uva.nl/u.endriss/seminar/.

Join in person or online via Zoom: https://uva-live.zoom.us/j/63449968266