A symbolic dynamic programming approach for modelling first-order Markov decision processes within the fluent calculus is given. Based on an idea initially presented in [3], the major components of Markov decision processes such as the optimal value function and a policy are logically represented. The technique produces a set of first-order formulae with equality that minimally partitions the s...

The goal of this paper is to translate (fragments of) the quantified discrete duration calculus QDDC, proposed by P. Pandya, into symbolic acceptors with counters. Acceptors are written in the synchronous programming language Lustre, in order to allow available symbolic verification tools (model-checkers, abstract interpreters) to be applied to properties expressed in QDDC. We show that importa...

This article contributes to developing a management and organisation studies perspective on political organising by focusing on: (a) populism; (b) the exercise of power; (c) politics. We address two questions: in what ways have English populist politicians 20th 21st centuries utilised language along with other aspects campaign build enhance their symbolic power? And: how do organisations conver...

Decision-tree algorithms provide one of the most popular methodologies for symbolic knowledge acquisition. The resulting knowledge, a symbolic decision tree along with a simple inference mechanism, has been praised for comprehensibility. The most comprehensible decision trees have been designed for perfect symbolic data. Classical crisp decision trees (DT) are widely applied to classification t...

Similarly to other connectionist models, Graph Neural Networks (GNNs) lack transparency in their decision-making. A number of sub-symbolic approaches have been developed provide insights into the GNN decision making process. These are first important steps on way explainability, but generated explanations often hard understand for users that not AI experts. To overcome this problem, we introduc...

In this paper, we present VATA, a versatile and efficient open-source tree automata library applicable, e.g., in formal verification. The library supports both explicit and semi-symbolic encoding of non-deterministic finite tree automata and provides efficient implementation of standard operations on both. The semi-symbolic encoding is intended for tree automata with large alphabets. For storin...

In the past, a variety of computational problems have been tackled with different connectionist network approaches. However, very little research has been done on a framework which connects neuroscience-inspired models with connectionist models and higher level symbolic processing. In this paper, we outline a preference machine framework which focuses on a hybrid integration of various neural a...