A NEW APPROACH TO THE RULE-BASED SYSTEMS DESIGN AND IMPLEMENTATION PROCESS

The paper discusses selected problems encountered in practical rule-based systems (RBS) design and implementation. To solve them XTT, a new visual knowledge representation is introduced. Then a complete, integrated RBS design, implementation and analysis methodology is presented. This methodology is supported by a visual CASE tool called Mirella.The main goal is to move the design procedure to a more abstract, logical level, where knowledge specification is based on use of abstract rule representation. The design specification is automatically translated into Prolog code, so the designer can focus on logical specification of safety and reliability. On the other hand, system formal aspects are automatically verified on-line during the design, so that its verifiable characteristics are preserved

Loki : the semantic wiki for collaborative knowledge engineering

We present Loki, a semantic wiki designed to support the collaborative knowledge engineering process with the use of software engineering methods. Designed as a set of DokuWiki plug-ins, it provides a variety of knowledge representation methods, including semantic annotations, Prolog clauses, and business processes and rules oriented to specific tasks. Knowledge stored in Loki can be retrieved via SPARQL queries, in-line Semantic MediaWiki-like queries, or Prolog goals. Loki includes a number of useful features for a group of experts and knowledge engineers developing the wiki, such as knowledge visualization, ontology storage, or code hint and completion mechanism. Reasoning unit tests are also introduced to validate knowledge quality. The paper is complemented by the formulation of the collaborative knowledge engineering process and the description of experiments performed during Loki development to evaluate its functionality. Loki is available as free software at https://loki.re

Artificial intelligence research community and associations in Poland

In last years Artificial Intelligence presented a tremendous progress by offering a variety of novel methods, tools and their spectacular applications. Besides showing scientific breakthroughs it attracted interest both of the general public and industry. It also opened heated debates on the impact of Artificial Intelligence on changing the economy and society. Having in mind this international landscape, in this short paper we discuss the Polish AI research community, some of its main achievements, opportunities and limitations. We put this discussion in the context of the current developments in the international AI community. Moreover, we refer to activities of Polish scientific associations and their initiative of founding Polish Alliance for the Development of Artificial Intelligence (PP-RAI). Finally two last editions of PP-RAI joint conferences are summarized

Local Universal Rule-based Explanations

Explainable artificial intelligence (XAI) is one of the most intensively developed are of AI in recent years. It is also one of the most fragmented one with multiple methods that focus on different aspects of explanations. This makes difficult to obtain the full spectrum of explanation at once in a compact and consistent way. To address this issue, we present Local Universal Explainer (LUX) that is a rule-based explainer which can generate factual, counterfactual and visual explanations. It is based on a modified version of decision tree algorithms that allows for oblique splits and integration with feature importance XAI methods such as SHAP or LIME. It does not use data generation in opposite to other algorithms, but is focused on selecting local concepts in a form of high-density clusters of real data that have the highest impact on forming the decision boundary of the explained model. We tested our method on real and synthetic datasets and compared it with state-of-the-art rule-based explainers such as LORE, EXPLAN and Anchor. Our method outperforms currently existing approaches in terms of simplicity, global fidelity and representativeness

Leukemia and chromosomal instability in aged Fancc−/− mice

Fanconi anemia (FA) is an inherited disorder of genomic instability associated with high risk of myelodysplasia and acute myeloid leukemia (AML). Young mice deficient in FA core complex genes do not naturally develop cancer, hampering preclinical studies on malignant hematopoiesis in FA. Here we describe that aging Fancc−/− mice are prone to genomically unstable AML and other hematologic neoplasms. We report that aneuploidy precedes malignant transformation during Fancc−/− hematopoiesis. Our observations reveal that Fancc−/− mice develop hematopoietic chromosomal instability followed by leukemia in an age-dependent manner, recapitulating the clinical phenotype of human FA and providing a proof of concept for future development of preclinical models of FA-associated leukemogenesis

The N-terminal domain of human GATA1 prevents dyserythropoietic anemia and megakaryocyte dysplasia in vivo

We describe a child with dyserythropoietic anemia, thrombocytosis, functional platelet defect, and megakaryocyte dysplasia. We show that (i) this constellation of hematopoietic abnormalities was due to a germline mutation within the 5′ untranslated region (5′UTR) of globin transcription factor 1 (GATA1); (ii) the mutation impaired a 5′UTR GATA1 splicing site, with promoted production of the shortened GATA1 isoform lacking the N-terminus; and (iii) expression of the GATA1 N-terminus is restricted to erythroblasts and megakaryocytes in normal marrow, consistent with the patient's abnormal erythropoiesis and megakaryopoiesis. Our findings provide insights into the clinically relevant in vivo function of the N-terminal domain of GATA1 in human hematopoiesis

Applying affective design patterns in VR firefighter training simulator

We present a prototype of virtual reality training simulator for firefighters. Our approach is based on the concept of Affective Patterns in Serious Games. One of the most serious problems when it comes to training firefighters is to maintain the right level of their commitment. The idea to solve the problem of repetitive and monotonous exercises is to combine them with those implemented in VR. While creating the solution for optimizing a psychological background of knowledge acquisition in training, we used concepts from the Motivational Intensity Theory