Nash equilibrium is one of the most fundamental solution concepts in game theory, where we know its existence in any finite game. In this project, we are interested in the computation of a Nash equilibrium in the specific class of bimatrix zero-sum games. We will study learning algorithms for computing (approximate) Nash equilibria in zero-sum … full description “Algorithms for Nash equilibria in zero-sum games (available)”
Category: Algorithms
Building a Benchmark Suite for Modal Mu-Calculus (available)
The modal mu-calculus [1] is a logic for expressing properties of abstract state transition systems, and generalises other logics like Linear Temporal Logic (LTL) and Computation Tree Logic (CTL). Because of this, it is a very useful tool for describing and verifying the behaviour of computer systems. The aim of this project is to support … full description “Building a Benchmark Suite for Modal Mu-Calculus (available)”
Deciding Isomorphism for Infinite Descent Problems (available)
The Infinite Descent property underpins two very important applications in program verification: termination of programs [1,2], on the one hand, and correctness of cyclic proofs of formulas or properties [3], on the other. In both cases, the object of interest (i.e. a program or a proof) is converted into an abstract form for which the … full description “Deciding Isomorphism for Infinite Descent Problems (available)”
Embeded programming for INTI (available)
We are building a low-power transputer (parallel computer with microcontrollers) to study neuromorphic computing and run inference in low power devices (low power as in low computing power and low energy consumption). It is named the Incipient Neuromorphic Transputer Initiatiave in honour of Inti the Inca sun god. And because it is an incipient effort … full description “Embeded programming for INTI (available)”
Entry into the PACE Parameterized Algorithms and Computational Experiments Challenge (completed)
Parameterized Complexity is a research field that, by its own self-description, strives to provide practical, yet theoretically well-founded ways to deal with computationally hard problems (e.g., so-called NP-hard problems). However, the vast majority of the work in the field is purely theoretical — there is a great toolbox of interesting and powerful algorithmic methods, which have been proven to have … full description “Entry into the PACE Parameterized Algorithms and Computational Experiments Challenge (completed)”
Machine Learning for Crystal Structure Prediction (completed)
Crystal Structure Prediction (CSP) is one of the major problems in computational chemistry with numerous applications in real life. This is essentially the (global) minimisation of a continuous, high-dimensional, complicated function. Many heuristic methods have been proposed for CSP and recently new methods based on Machine Learning were introduced. The goal of this project is … full description “Machine Learning for Crystal Structure Prediction (completed)”