Frieder Stolzenburg

Hochschule Harz · Department of Automation and Computer Sciences

Negation is both an operation in formal logic and in natural language by which a proposition is replaced by one stating the opposite, as by the addition of “not” or another negation cue. Treating negation in an adequate way is required for cognitive reasoning, which aims at modeling the human ability to draw meaningful conclusions despite incomplet...

Recurrent neural networks are a powerful means in diverse applications. We show that, together with so-called conceptors, they also allow fast learning, in contrast to other deep learning methods. In addition, a relatively small number of examples suffices to train neural networks with high accuracy. We demonstrate this with two applications, namel...

Recurrent neural networks are a powerful means in diverse applications. We show that, together with so-called conceptors, they also allow fast learning, in contrast to other deep learning methods. In addition, a relatively small number of examples suffices to train neural networks with high accuracy. We demonstrate this with two applications, namel...

Negation is both an operation in formal logic and in natural language by which a proposition is replaced by one stating the opposite, as by the addition of "not" or another negation cue. Treating negation in an adequate way is required for cognitive reasoning, which comprises commonsense reasoning and text comprehension. One task of cognitive reaso...

The CoRg system is a system to solve commonsense reasoning problems. The core of the CoRg system is the automated theorem prover Hyper that is fed with large amounts of background knowledge. This background knowledge plays a crucial role in solving commonsense reasoning problems. In this paper we present different ways to use knowledge graphs as ba...

The CoRg system is a system to solve commonsense reasoning problems. The core of the CoRg system is the automated theorem prover Hyper that is fed with large amounts of background knowledge. This background knowledge plays a crucial role in solving commonsense reasoning problems. In this paper we present different ways to use knowledge graphs as ba...

The main goal of this work is to facilitate machine learning research for multi-robot systems as they occur in RoboCup, an international scientific robot competition. We describe our software (a simulator patch and scripts) and a larger research dataset from games of some of the top teams from 2016 and 2017 in Soccer Simulation League (2D), where t...

Commonsense reasoning is a difficult task for a computer to handle. Current algorithms score around 80% on benchmarks. Usually these approaches use machine learning which lacks explainability, however. Therefore, we propose a combination with automated theorem proving here. Automated theorem proving allows us to derive new knowledge in an explainab...

The term cognitive computing refers to new hardware and/or software that mimics the functioning of the human brain. In the context of question answering and commonsense reasoning this means that the reasoning process of humans shall be modeled by adequate technical means. However, since humans do not follow the rules of classical logic, a system de...

The adjective cognitive especially in conjunction with the word computing seems to be a trendy buzzword in the artificial intelligence community and beyond nowadays. However, the term is often used without explicit definition. Therefore we start with a brief review of the notion and define what we mean by cognitive reasoning. It shall refer to mode...

Recurrent neural networks are a powerful means to cope with time series. We show that already linearly activated recurrent neural networks can approximate any time-dependent function f(t) given by a number of function values. The approximation can effectively be learned by simply solving a linear equation system; no backpropagation or similar metho...

RoboCup is an international scientific robot competition in which teams of multiple robots compete against each other. Its different leagues provide many sources of robotics data, that can be used for further analysis and application of machine learning. This paper describes a large dataset from games of some of the top teams (from 2016 and 2017) i...

We present a new approach for identifying situations and behaviours, which we call "moves", from soccer games in the 2D simulation league. Being able to identify key situations and behaviours are useful capabilities for analysing soccer matches, anticipating opponent behaviours to aid selection of appropriate tactics, and also as a prerequisite for...

In the middle of the 1980s, David Poole introduced a semantic, model-theoretic notion of specificity to the artificial-intelligence community. Since then it has found further applications in non-monotonic reasoning, in particular in defeasible reasoning. Poole tried to approximate the intuitive human concept of specificity, which seems to be essent...

The fields of neural computation and artificial neural networks have developed much in the last decades. Most of the works in these fields focus on implementing and/or learning discrete functions or behavior. However, technical, physical, and also cognitive processes evolve continuously in time. This cannot be described directly with standard archi...

This book constitutes the refereed conference proceedings of the 10th International Conference on Multi-disciplinary Trends in Artificial Intelligence, MIWAI 2016, held in Chiang Mai, Thailand, in December 2016. The 22 revised full papers presented together with 5 short papers and 2 abstracts of invited talks were carefully reviewed and selected fr...

Higher-level cognition is one of the constituents of our human mental abilities and subsumes reasoning, planning, language understanding and processing, and problem solving. A deeper understanding can lead to core insights to human cognition and to improve cognitive systems. There is, however, so far no unique characterization of the processes of h...

Higher-level cognition includes logical reasoning and the ability of question answering with common sense. Our RatioLog project addresses the problem of rational reasoning in deep question answering by methods from automated deduction and cognitive computing. In a first phase, we combine techniques from information retrieval and machine learning to...

Deontic logic is a very well researched branch of mathematical logic and philosophy. Various kinds of deontic logics are considered for different application domains like argumentation theory, legal reasoning, and acts in multi-agent systems. In this paper, we show how standard deontic logic can be used to model ethical codes for multi-agent system...

Deontic logic is a very well researched branch of mathematical logic and philosophy. Various kinds of deontic logics are discussed for different application domains like argumentation theory, legal reasoning, and acts in multi-agent systems. In this paper, we show how standard deontic logic can be stepwise transformed into description logic and DL-...

This paper briefly characterizes the field of cognitive computing. As an exemplification, the field of natural language question answering is introduced together with its specific challenges. A possibility to master these challenges is illustrated by a detailed presentation of the LogAnswer system, which is a successful representative of the field...

In the middle of the 1980s, David Poole introduced a semantical, model-theoretic notion of specifity to the artificial-intelligence community. Since then it has found further applications in non-monotonic reasoning, in particular in defeasible reasoning. Poole tried to approximate the intuitive human concept of specifity, which seems to be essentia...

The perception of consonance/dissonance of musical harmonies is strongly correlated to their periodicity. This is shown in this article by consistently applying recent results from psychophysics and neuroacoustics, namely that the just noticeable difference of human pitch perception is about 1% for the musically important low frequency range and th...

Recognizing objects from images becomes a more and more important research and application topic. There are diverse applications such as face recognition, analysis of aerial images from multicopters, object tracking, image-based web search, etc. Many existing approaches focus on shape retrieval from a single polygon of contour points, or they try t...

Each object in a digital image is composed of many patches (segments) with different shapes and colors. In order to recognize an object, e.g. a table or a book, it is necessary to find out which segments are typical for which object and in which segment neighborhood they occur. If a typical segment in a characteristic neighborhood is found, this se...

Three of the major problems in qualitative spatial rea-soning and robotics are localization, exploration, and navigation in known or unknown environments. This paper investigates how far different qualitative methods based on angle information, most of them originally invented for the representation of spatial knowledge only, are well-suited for th...

We present a tool environment with a constraint logic programming core, that allows us to specify multi-agent systems graphically and verify them automatically. This combines the advantages of graphical notations from software engineering and formal methods. We demonstrate this on a Robocup rescue scenario.

In this chapter, we have shown a framework to formally specify and verify physical multiagent systems by means of hybrid automata, especially for those agents that are defined through their capability to continuously react to a physical environment, while respecting some time constraints. The framework provided two different views of behaviors' spe...

Empirical results demonstrate, that human subjects rate harmonies, e.g. major and minor triads, differently with re- spect to their sonority. These judgements of listeners have a strong psychophysical basis. Therefore, harmony percep- tion often is explained by the notions of dissonance and tension, computing the consonance of one or two intervals....

This chapter discusses a top-down approach to modelling soccer knowledge, as it can be found in soccer theory books. The goal is to model soccer strategies and tactics in a way that they are usable for multiple robotic soccer leagues in the RoboCup. We investigate if and how soccer theory can be formalized such that specifi cation and execution are...

This paper presents a method for engineering and programming multi- robot systems, based on a combination of statecharts and hybrid automata, which are well-known in the fields of software engineering and arti ficial intelligence. This formal specification method allows graphical presenta tion of the whole mul- tiagent system behavior. In addition,...

Formal methods for multi-robot system analysis, especially logic-based methods, operate on discrete models. Optimization methods for simultaneous trajectory and task allocation, namely mixed in-teger dynamic optimization, operate on hybrid dynamical models which take into account a model of the motion dynamics of the physical robot. In this paper,...

Hybrid systems are the result of merging the two most commonly used models for dynamical systems, namely continuous dynamical systems defined by differential equations and discrete-event systems defined by automata. One can view hybrid systems as constrained systems, where the constraints are used to describe the possible process flows, invariants,...

This paper shows how multiagent systems can be modeled by a com- bination of UML statecharts and hybrid automata. This allows formal system specification on different levels of abstraction on the one h and, and expressing real-time system behavior with continuous variables on the other hand. It is shown how multi-robot systems can be modeled by hyb...

This paper shows how multiagent systems can be modeled by a combination of UML statecharts and hybrid automata. This allows formal system specification on different levels of abstraction on the one hand, and expressing real-time system behavior with continuous variables on the other hand. It is not only shown how multi-robot systems can be modeled...

In multi-robot systems, the need for precise modeling or specification of agent behaviors arises due to the high complexity of the robot agent interactions and the dynamics of the environment. Since the behavior of agents usually can be understood as driven by external events and internal states, it is obvious to model multiagent systems by state t...

The paper discusses a top-down approach to model soccer knowledge, as it can be found in soccer theory books. The goal is to model soccer strategies and tactics in a way that they are usable for multiple RoboCup soccer leagues, i.e. for different hardware platforms. We investigate if and how soccer theory can be formalized such that specification a...

A matching is a (one-to-one) mapping between two sets, satisfying some given constraints. In a multiagent scenario, i.e. in a setting where at least one of the sets corresponds to a group of agents, a number of interesting facets are added to this general matching problem. Therefore, in this paper, we discuss several different matching criteria, wh...

In order to design and implement multiagent systems, the specification method should be as expressive and comprehensive as possible. Statecharts, which are capable of describing dynamic systems and are widely accepted in the computer science community, are applied and investigated for this objective. In this paper, multiagent systems are studied in...

This paper relates the Defeasible Logic Programming (DeLP) framework and its semantics to classical logic programming frameworks. In DeLP, we distinguish between two different sorts of rules: strict and defeasible rules. Negative literals (∼A) in these rules are considered to represent classical negation. In contrast to this, in normal logic progra...

Most formalisms for representing common-sense knowledge allow incomplete and potentially inconsistent information. When strong negation is also allowed, contradictory con-clusions can arise. A criterion for deciding between them is needed. The aim of this paper is to investigate an inherent and autonomous comparison criterion, based on specificity...

In many approaches for qualitative spatial reasoning, navigation of an agent in a more or less static environment is considered (e.g. in the double-cross calculus [13]). However, in general, the environment is dynamic, which means that both the agent itself and also other objects and agents in the environment may move. Thus, in order to perform spa...

Multiagent systems are a promising new paradigm in computing, which are contributing to various fields. Many theories and technologies have been developed in order to design and specify multiagent systems, however, no standard procedure is used at present. Industrial applications often have a complex structure and need plenty of working resources....

The RoboLog Team. The RoboLog team participated in the simulator competitions in 1999 (Stockholm), 2000 (Melbourne), and 2001 (Seattle). 3 people, Jan Murray, Oliver Obst and Frieder Stolzenburg (team leader), form the core of the team. There are cur-rently 7 additional members, namely Heni Ben Amor, Joschka B篓odecker, Marion Lev-elink, Jana Lind,...

In this paper, we present a multi-layered architecture for spatial and temporal agents. The focus is laid on the declarativity of the approach, which makes agent scripts expressive and well understandable. They can be realized as (constraint) logic programs. The logical description language is able to express actions or plans for one and more auton...

Building agents for a scenario such as the RoboCup simulation league requires not only methodologies for implementing high-level complex behavior, but also the careful and efficient programming of low-level facilities like ball interception. With this hypothesis in mind, the development of RoboLog Koblenz has been continued. As before, the focus is...

Outline. A formalism for the specification of multiagent systems should be expressive enough to model not only the behavior of one single agent, but also the collaboration among several agents and the influences caused by external events. For this, state machines [4] seem to provide an adequate means. Therefore, the approach of the team RoboLog Kob...

In this paper, we present a multi-layered architecture for spatial and temporal agents. Agent scripts can be realized as (constraint) logic programs. The logical description language is able to express actions or plans for one and more autonomous and cooperating agents for the RoboCup (Simulator League). We focus on the presentation of the script l...

A formalism for the specification of multiagent systems should be expressive and illus-trative enough to model not only the behavior of one single agent, but also the collaboration among several agents and the influences caused by external events from the environment. For this, state machines [19] seem to provide an adequate means. Furthermore, it...

. Impressive work has been done in the last years concerning the meaning of negation and disjunction in logic programs, but most of this research concentrated on propositional programs only. While it suffices to consider the propositional case for investigating general properties and the overall behaviour of a semantics, we feel that for real appli...

the partial evaluation property (GPPE) adapted for disjunctive programs. Unfortunately, GPPE is not sound for rules with variables because of the occurrence of unifiable atoms in the heads of rules. We make the GPPE sound by introducing equational constraints [6]. This im- This research is partly supported by a grant from the German science foundat...

Building agents for a scenario such as the RoboCup simulation league requires not only methodologies for implementing high-level complex behavior, but also the careful and efficient programming of low-level facilities like ball interception. With this hypothesis in mind, we continued the development of RoboLog Koblenz. As before, the focus is laid...

Machine that extends the WAM to handle defeasible reasoning is available in the Argentinian group: the Justification Abstract Machine. The language for these programs contains defeasible rules to capture tentative knowledge and reasoning. It allows the representation of incomplete and potentially inconsistent information, and uses the defeasible ar...

. Most formalisms for representing common-sense knowledge allow incomplete and potentially inconsistent information. When strong negation is also allowed, contradictory conclusions can arise. Therefore, a criterion for deciding between them is needed. Several extensions of logic programming consider priorities over program (default) rules. However,...

Building agents for the RoboCup simulation league requires not only methodologies for implementing high-level complex behavior, but also the careful and efficient programming of low-level facilities, such as ball interception. With this hypothesis in mind, we continued the development of RoboLog Koblenz, which participated in the simulator league i...

The RoboCup scenario yields a variety of fields of research. The main goal of the RoboLog project, undertaken at the University of Koblenz in Germany, is the specification and implementation of flexible agents in a declarative manner. The agents should be able to deal with the real-time requirements but also be capable of more complex behavior, inc...

this article is to argue that automated deduction systems can be usefully applied in practice, but it is necessary to have available a variety of deduction methods, to understand their properties and their computational power in order to tailor them for the application under consideration. In the early days of automated deduction, research concentr...

In this paper, we present a multi-layered architecture for spatial agents. The focus is laid on the declarativity of the approach, which makes agent scripts expressive and well understandable. They can be realized as (constraint) logic programs. The logical description language is able to express actions or plans for one and more autonomous and coo...

Automated reasoning systems often suffer from redundancy: similar parts of derivations are repeated again and again. This leads us to the problem of loop-detection, which clearly is undecidable in general. Nevertheless, we tackle this problem by extending the hyper-tableau calculus as proposed by Baumgartner (1998) by generalized terms with exponen...

In this paper, an algorithm for set unification – which is a restricted case of the associative-commutative-idempotent (ACI) unification – is presented. The algorithm is able to unify finite sets containing arbitrary terms. It is nondeterministic and can easily be implemented in Prolog. Because of the simplicity of the algorithm, the computation of...

Vom 29.Juli bis zum 4.August 1999 fand in Stockholm zusammen mit der IJCAI'99 die drit-te Weltmeisterschaft im Roboterfu?ball RoboCup statt. Der RoboCup ist ein Versuch, die Forschung auf dem Gebiet der KI und der Robotik zusammen-zuf¨uhren, indem ein Standard-Szenario angeboten wird, n¨amlich die Simulation eines Fu?ballspiels, das einen explizite...

In automated deduction, the final goal is to achieve a fully automatic proof system: given a logical specification of a problem, take a high-performance theorem prover, and let it do the work. Unfortunately, this does not work in practice, not only because theorem provers often lack finding the proof within reasonable time, but also because the spe...

Theorem proving, logic programming and constraint solving can be combined in a straightforward manner. This is shown not only by setting up a theoretical framework, but also by a real world application: the calculation of banking fees. We tackle the problems of deciding whether such a rule set is total and deterministic, i.e. does it permit calcula...

Impressive work has been done in the last years concerning the meaning of negation and disjunction in logic programs, but most of this research concentrated on propositional programs only. While it suffices to consider the propositional case for investigating general properties and the overall behavior of a semantics, we feel that for real applicat...

We demonstrate that theorem provers using model elimination (ME) can be used as answer-complete interpreters for disjunctive logic programming. More specifically, we introduce a family of restart variants of model elimination and we introduce a mechanism for computing answers. Building on this, we develop a new calculus called ancestry restart ME....

. In computational linguistics, we are often interested in developing grammar formalisms declaratively. However, tractability often becomes a problem then. Therefore, we want to argue for the use of constraint logic programming (CLP), and it is yet interesting to note that most logic based natural language systems have not attempted to employ CLP....

Constraint logic programming combines Horn-clause logic and constraint reasoning. However, the specification of many problems often requires disjunctive, i.e. non-Horn rules in addition. There are approaches proposing such an extension of logic programming, but first and foremost they provide theoretical frameworks only. Here, we want to introduce...

In computational linguistics, we are often interested in developing grammar formalisms declaratively. However, tractability often becomes a problem then. Therefore, we want to argue for the use of constraint logic programming (CLP), and it is yet interesting to note that most logic based natural language systems have not attempted to employ CLP. Ou...