History

Applied Logic Laboratory (ALL) is a Hungarian R&D SME company established in 1986. Its main research areas include include computer science, artificial intelligence, cognitive systems, modelling of systems of high complexity, medical and biological informatics.. The company unites expertise in system modelling and design, knowledge engineering, signal processing, neural computing, data analysis and data mining, natural language processing, and decision support.

In computer science ALL dealt with the development of formal theoretical methods to charactarise programs, programming languages of different programming paradigms and software engineering. It developed a constructive specification theory as a possible way of declarative programming. Program specification methods are investigated which, through their constructivity, can be realized and used as prototypes. ALL also delt with with problem oriented computer architecture by developing different architectures adequate to different problem classes and also by developing a universal architecture, which can be adopted to the actual problem class.

In artificial intelligence ALL deals with both theoretical and practical problems. The theoretical questions are mainly related to the theory of problem solving, theory of (reliable and plausible) reasoning, machine learning and knowledge acquisition. The practical problems are related to the development of intelligent assistant systems, decision support systems, high performance knowledge bases and distributive and co-operative intelligent systems.

ALL has developed special tools and methods for efficient knowledge management and intelligent data analysis. Special methods were provided to formalise hardly formalisable problem domains and disciplines and manage the extracted knowledge together with the existing knowledge. Innovative methods were developed to analyse experimental data in order to extract information e.g. in the form of laws and relationships. Special tools were developed on the basis of various formalisms depending of the “world view” of the corresponding problem domains. Thus logic based, fuzzy, probabilistic methods and also connectionistical methods were developed. The methods have been applied to the problems of geoinformation systems, medical-, bio- and neuroinformatics.

The developed methods of intelligent data analysis have been successfully used in biomedical informatics and in sociological studies e.g. to process the experimental data in order to extract new information and knowledge.

ALL is also active in ontology development.

ALL has worked out special methods for knowledge processing and knowledge transfer for E-learning. The knowledge transfer methods deel with the organisation of the learning and teaching processes and with their intelligent support. Special interest was devoted to the inrease of the efficiency of the education processes due to special support by intelligent systems.

In cognitive systems ALL is active in development of various methods of plausible reasoning including statistical, logical and fuzzy logic methods, case-based reasoning and methods based on analogy. These methods are used to realise abduction, deduction and induction for reasoning.

The reasoning methods developed and applied includes several methods for data mining and knowledge extraction:

• Statistical methods (used in geological and medical expert systems).
• Plausible logical methods (used in pharmacological design system and diagnostic system).
• Neuron network (used in medical decision support system).

Special approach has been suggested that allows to synthetise the processes of cognitive reasoning from the various reasoning operators.

ALL is specialised for developing knowledge based systems such as digital assistants, decision support systems, high performance knowledge bases and distributive and co-operative intelligent systems e.g. in different medical consultation and critiquing services.

In the field of modelling sytems of high complexity ALL is elaborating the descriptive and analytical methods and tools for non-linear dynamic systems and tools for logic modelling and also their application within the field of biomedicine. ALL’s researches within the field of medicine comprise the characterization and modelling of the entire living organism, elaborating new test methods in order to provide a better diagnosis and a more optimal treatment. Special methods and tools have been developed for modelling processes of living systems, such as the neural network that consists of active neurons.

ALL has also been involved in modelling geological and geophysical processes and the related methods of reasoning. Results of these had been implemented in intelligent geo-infomation systems.

ALL has been working on modelling economic and social processes by the use of original connectionistic and self-organising methods and tools. The obtained results have been used for forcasting complex micro- and macro-economic processes.

In medical informatics ALL has developed innovative techniques for representing biomedical knowledge, modelling homeostatic processes and formalising medical reasoning. It has been very active in developing tools that support medical problem solving. These techniques have been implemented as parts of advanced information systems in nephrology, immunology, cardiology, pulmonology and traumatology.

ALL is specialised in developing knowledge based systems such as digital assistants, decision support systems, high performance knowledge bases and distributive and co-operative intelligent systems in different medical consultation and critiquing services. The company also offers comprehensive quality management tools.

ALL has participated in the development of a methodology and environment for knowledge based medical systems, named “partner systems”(PS). PS includes special tools for information modelling and threshold logic based decision making. Within this frame several medical systems have been developed, among others a system supporting decision making in every phase of the care.

Over the recent years ALL has been focusing on delivering individualised care and patient-centred re-engineering of health care institutions. It has developed complex models, test methods and inference techniques for refining diagnostic descriptions and selecting customised optimal treatment. ALL has been active in developing intelligent sensors for monitoring physiological and psychophysiological parameters and interpreting data they provided. ALL has also developed new models of patient-centred innovative health care organisations.

Its staff which includes academics, research scientists, software developers, engineers, and medical experts, has published more than 10 books, and more than 200 papers in peer reviewed scientific journals and conference proceedings.

The company has been involved in many national, international and several EU-funded projects. In recent projects ALL was involved in intelligent data analysis in diabetes care (M2DM project) and modelling embedded systems (REDEST project).