Learning Mechanisms on OWL-S Service Descriptions for Automated Action Selection

Johannes Fähndrich, Nils Masuch, Lars Borchert, and Sahin Albayrak. Presented at the Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017. http://ioa.alqithami.com/2017/IoA'17-Proceedings.pdf#page=62

Abstract: With the increase complexity of IoT systems, the well known development paradigm for software development like Service Oriented Architectures and Multi Agent Systems have to be adapted to t the now challenges of IoT environments. Here the vast amount of available components and the speci c implementation for special purpose hardware calls for an abstraction of functionality as well as to new development tools which allow to handle the dynamism of IoT applications. Here a multitude of special purpose sensors with view computational resources have to be combined to create emerging software. Most of the hardware reaches an return of investment only o ering its service to third party developers. For a developer to be able to integrate those services into an application, a adaptive search mechanism need to be developed, which is able to specialize in the di erent domains of e.g. IoT applications.

A Multi-Agent Platform for Augmented Reality based Product-Service Systems

Nils Masuch, Tobias Küster, Johannes Fähndrich, Marco Lützenberger, and Sahin Albayrak. Presented at the Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, 2017. http://dl.acm.org/citation.cfm?id=3091443

Abstract: Advances in the IT-sector have shifted the conventional development of products into the direction of integrated product- service systems. Product-service systems promise a long(er) lifetime due to latest versions of (software-based) services that operate on the purchased hardware. Furthermore, they can be extremely adaptable and thus ensure connectivity and compatibility to other existing or future systems. The aim of this demo is twofold. First, the demo shows that a multi-agent approach is perfectly suited to meet the requirements for product-service systems. Second, we present a complete development environment to easily specify and deploy agent-based solutions, especially for UIoriented processes involving Augmented Reality technology.

Design and Use of a Semantic Similarity Measure for Interoperability Among Agents

Fähndrich, J., Weber, S. Ahrndt, S. (2016). Presented at the 14th German Conference on Multiagent System Technologies. Springer International Publishing, 2016. http://doi.org/10.1007/978-3-319-45889-2_4

Abstract: The capability to identify the sense of polysemic words, i.e. words that have multiple meanings, is an essential part of intelligent systems, e.g. when updating an agent's beliefs during conversations. This process is also named Word Sense Disambiguation (WSD) and is approached by applying semantic similarity measures. Within this work, we present an algorithm to create such a semantic similarity measure using marker passing, that: (1) generates a semantic network out of a semantic service description, (2) sends markers through the networks to tag sub-graphs that are of relevance, and (3) uses these markers to create a semantic similarity measure. We will discuss the properties of the algorithm, elaborate its performance with di erent part of speech, and discuss the lifted properties for the algorithm to be used in WSD. To evaluate our approach, we compare it to state-of-the-art measures using the Rubinstein1965 and WordSim353 dataset. It is shown, that our approach outperforms these state-of-the-art measures and, further, is able to adapt the predictions to the contextual information.

Semantic Service Management for Enabling Adaptive and Evolving Processes

Fähndrich, J., Küster, T., Masuch, N. (2016). (Vol. 6, pp. 1–15). Presented at the 11th Int. Conf. on Internet and Web Applications and Services (ICIW 2016).

Abstract: With the rise of new paradigms like the Internet of Things, where thousands of devices and services of different providers are to be connected to complex processes, service-oriented approaches come to the fore. However, current solutions still lack of comprehensive methodologies how to dynamically manage and combine services to fulfil the given goals. In this paper we present a semantic-based service management methodology that enables the semantic description of services and provides an automatic service discovery and composition solution at design- and runtime. Furthermore, we present development tools that support the usage of semantic web technologies and we describe an execution environment where the approach is embedded. We conclude with an evaluation scenario from an e-mobility research project.

Multi-Agent System in Practice -- When Research Meets Reality.

Lützenberger, M., Kuester, T., Masuch, N., & Fähndrich, J. (2016). In J. Thangarajah, K. Tuyls, C. Jonker, & S. Marsella (Eds.), (pp. XX–YY). Presented at the Proceedings of the 15th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2016), Singapore.

Abstract: The applicability and usefulness of agent technology for real world problems is still a matter of discussion---even within the AAMAS community. While theoretical models have significantly matured and led to an exciting variety of results, there were only few attempts to validate these models in reality. In this paper we aim to report on challenges that occurred when agent theory was used to approach real world problems. In doing so, we focus on the concept of planning, since planning currently appears to be one of the most relevant concepts for distributed real world applications. We examine four agent-based applications and emphasise problems that occurred when agent theory was practically applied. We also show how these problems were countered and propose more general solutions based on theses tailored and context-specific approaches. The aim of this paper is to bring the two diverging branches of agent theory and practice back together in order to better adapt agent technology to the requirements of professional software.

Self-Explanation through Semantic Annotation and (automated) Ontology Creation: A Survey

Fähndrich, J., Ahrndt, S., & Albayrak, S. (2015). (Vol. 6, pp. 1–15). Presented at the 10th International Symposium Advances in Artificial Intelligence and Applications, ACM. http://doi.org/10.15439/2015F416

Abstract: Semantic information is considered as foundation upon which modern approaches attempt to tackle the challenges of dynamic environments – service orchestration and ontology matching are two examples for the use of such information. Yet, many developers avoid the additional effort of adding semantic information (e.g., through annotations) to their data sets – limiting the reusability and interoperability of their Apps, services, or data. This problem is called the “knowledge acquisition bottleneck”, which can be addressed by providing suitable tool support. This survey analyses the state-of-the-art of such tools that support developers in the task of semantically enriching entities. Providing an overview of available tools from the early days until now, we particularly focus on the ‘level of automation’. Concluding that automation is very limited in contemporary tools we propose a concept that mixes connectionist and symbolic representation of meaning to decrease the manual effort.

Predictability in Human-Agent Cooperation: Adapting to Humans' Personalities

Ahrndt, S., Breitung, B., Fähndrich, J., & Albayrak, S. (2015). Predictability in Human-Agent Cooperation: Adapting to Humans' Personalities (Vol. 1, pp. 474–479). Presented at the SAC '15 Proceedings of the 30th Annual ACM Symposium on Applied Computing 2015, Salamanca, Spain: ACM Press. http://doi.org/10.1145/2695664.2695702

Abstract: Making artificial agents a constituent part of human activities leads to more affiliated teamwork scenarios and at the same time introduces several new challenges. One challenge is the team members' ability to be mutually predictable to each other, which is required to effectively plan own actions, e.g., in the field of human-aware planning. This work approaches the question whether agents are able to learn the personality of a human during interaction. In particular, we developed an agent model able to learn human personality during repeatedly played rounds in the Colored Trails Game. Human personality is described using a psychological theory of personality types known as the Five-Factor Model. The results indicate that some characteristics of a personality can be learned more accurately/easier than others.

A common approach to intelligent energy and mobility services in a smart city environment.

Lützenberger, M., Masuch, N., Kuester, T., Freund, D., Voß, M., Hrabia, C.-E., Pozo D., Fähndrich, J. Trollmann f., Keiser j., Albayrak S., (2015) Journal of Ambient Intelligence and Humanized Computing, 6(3), 337–350. http://doi.org/10.1007/s12652-015-0263-1

Abstract: Due to the fact that electric vehicles have not broadly entered the vehicle market there are many attempts to convince producers to integrate technologies that utilise embedded batteries for purposes different from driving. The vehicle-to-grid technology, for instance, literally turns electric vehicles into a mobile battery, enabling new areas of applications (e.g. to provide regulatory energy, to do grid-load balancing, or to buffer surpluses of energy) and business perspectives. Utilising a vehicle's battery, however is not without a price - in this case: the driver's mobility. Given this dependency, it is interesting that most available works consider the application of electric vehicles for energy and grid-related problems in isolation, that is, detached from mobility-related issues. The Distributed Artificial Intelligence Laboratory, or DAI-Lab, is a third-party funded research lab at Technische Universitat Berlin and integrates the chair for Agent Technologies in Business Applications and Telecommunication. The DAI-Lab has engaged in a large number of both, past and upcoming projects concerned with two aspects of managing electric vehicles, namely: energy and mobility. This article aims to summarise experiences that were collected during the last years and to present developed solutions which consider energy and mobility-related problems jointly.

Modelling of Personality in Agents: From Psychology to Logical Formalisation and Implementation.

Ahrndt, S., Fähndrich, J., Lützenberger, M., & Albayrak, S. (2015). In Bordini, Elkind, Weiss, Yolum (Eds.), (pp. 1691–1692). Presented at the Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, International Foundation for Autonomous Agents and Multiagent Systems.

Abstract: There is increasing interest in the agent community to integrate the concept of emotions and arti cial agents. The spectrum of available solutions reaches from applications and models of emotions to complete axiomatised logics. Despite the rich o er of solutions, available works neglect individual personality as a signi cant factor for the outcome of emotional behaviour pattern. However, di erent personalities a ect all relevant phases of human decision-making processes. In this paper, we introduce and discuss existing personality theories, propose a concept based on the beliefdesire- intention paradigm, and show how such concept can be implemented as prototype.

Are There Semantic Primes in Formal Languages?

Fähndrich, J., Ahrndt, S., & Albayrak, S. (2014). DCAI 11th International Symposium on Distributed Computing and Artificial Intelligence, 290(Chapter 46), 397–405. http://doi.org/10.1007/978-3-319-07593-8_46

Abstract: This paper surveys languages used to enrich contextual information with semantic descriptions. Such descriptions can be e.g. applied to enable rea- soning when collecting vast amounts of row data in domains like smart environments. In particular, we focus on the elements of the languages that make up their semantic. To do so, we compare the expressiveness of the well-known languages OWL, PDDL and MOF with a theory from linguistic called the Natural Semantic Metalanguage.

Formal Language Decomposition into Semantic Primes

Fähndrich, J., Ahrndt, S., & Albayrak, S. (2014). Adcaij: Advances in Distributed Computing and Artificial Intelligence Journal, 3(8), 56. http://doi.org/10.14201/ADCAIJ2014385673

Abstract: This paper describes an algorithm for semantic decomposition. For that we surveys languages used to enrich contextual information with semantic descriptions. Such descriptions can be e.g. applied to enable reasoning when collecting vast amounts of information. In particular, we focus on the elements of the languages that make up their semantic. To do so, we compare the expressiveness of the well-known languages OWL, PDDL and MOF with a theory from linguistic called the Natural Semantic Metalanguage. We then analyze how the semantic of the language is build up and describe how semantic decomposition based on the semantic primes can be used for a so called mental lexicon. This mental lexicon can be used to reason upon semantic service description in the research domain of service match making.

Towards Automated Service Matchmaking and Planning for Multi-Agent Systems with OWL-S – Approach and Challenges

Fähndrich, J., Masuch, N., Yildirim, H., & Albayrak, S. (2014). In Service-Oriented Computing – ICSOC 2013 Workshops (Vol. 8377, pp. 240–247). Cham: Springer International Publishing. http://doi.org/10.1007/978-3-319-06859-6_21

Abstract: We advocate Self-Explanation as the foundation for the Self-* properties. Arguing that for system component to have such properties the underlining foundation is a awareness of them selfs and their environment. In the research area of adaptive software, self-* properties have shifted into focus pushing ever more design decisions to a applications runtime. Thus fostering new paradigms for system development like intelligent agents. This work surveys the state of the art methods of self-explanation in software systems and distills a definition of self-explanation.

HPLAN: Facilitating the Implementation of Joint Human-Agent Activities.

Ahrndt, S., Ebert, P., Fähndrich, J. , & Albayrak, S. (2014). In Y. Demazeau, F. Zambonelli, J. M. Corchado, & J. Bajo (Eds.), Advances in Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection. (Vol. 8473, pp. 1–12). Springer International Publishing. http://doi.org/10.1007/978-3-319-07551-8_1

Abstract: When it comes to planning for joint human-agent activities one has to consider not only a exible plan execution and social constraints but also the dynamic nature of humans. This can be done by providing additional information about a humans characteristics. For example, taking the physical and psychological condition of an elderly into consideration when developing collaborative applications like socially assistive robots. This work outlines Hplan, an extension to the agentframework JIAC V, that takes this requirement into account. HPLAN is strongly related to the conceptual model of dynamic planning components and integrates humans as avatars into a life cycle of planning, execution and learning.

Towards a Holistic Approach for Problems in the Energy and Mobility Domain

Luetzenberger, M., Masuch, N., Kuester, T., Keiser, J., Freund, D., Voß, M., Hrabia E-C., Pozo D., Fähndrich J., Trollmann F. & Albayrak S. (2014). Towards a Holistic Approach for Problems in the Energy and Mobility Domain. Procedia Computer Science, 32(0), 780–787. http://doi.org/10.1016/j.procs.2014.05.491

Abstract: We advocate Self-Explanation as the foundation for the Self-* properties. Arguing that for system component to have such properties the underlining foundation is a awareness of them selfs and their environment. In the research area of adaptive software, self-* properties have shifted into focus pushing ever more design decisions to a applications runtime. Thus fostering new paradigms for system development like intelligent agents. This work surveys the state of the art methods of self-explanation in software systems and distills a definition of self-explanation.

Human-Aware Planning: A Survey related to Joint Human-Agent Activities.

Ahrndt, S., Fähndrich, J., & Albayrak, S. (2014). In J. Bajo, J. M. Corchado, P. Mathieu, A. Campbell, A. Ortega, E. Adam, et al. (Eds.), Trends in Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection. (Vol. 293, pp. 95–102). Springer International Publishing. http://doi.org/10.1007/978-3-319-07476-4_12

Abstract: To become a part of a joint human-agent team, arti cial agent are required to achieve joint goals with humans not only performing task for humans. This includes the ability to coordinate actions between team-members, which is e.g. addressed by Human-Aware Planning approaches. This work surveys available solutions regarding the special requirements identifi ed for joint human-agent activities. In articular, the work concentrates on the requirement of interpredictability, which requires to include the course of actions of other team-members into the planning process of one's own course of action.

Personalized Fall Risk Assessment Tool by using the Data Treasure contained in Mobile Electronic Patient Records.

Eryilmaz, E., Ahrndt, S., Fähndrich, J., & Albayrak, S. (2014). In C. Lovis, B. Seroussi, A. Hasman, L. Pape-Haugaard, O. Saka, & S. K. Andersen (Eds.), (Vol. 205, pp. 398–402). Presented at the e-Health - For Continuity of Care, IOS Press. http://doi.org/10.3233/978-1-61499-432-9-1270

Abstract: This work presents a novel approach for combining multiple Electronic Patient Records (EPRs) to a self-learning fall risk assessment tool. This tool is used by a new type of home-visiting nurses to track the fall risk of their patients. In order to provide personalized healthcare for elderly people, we combine multiple EPRs using an agent-based architecture, where each patient is represented by an associated agent. The patient agents are enabled to negotiate about possible fallrisk indicators recognized in the specific patient population under care. We use distributed information fusion and opinion aggregation techniques to elaborate new fall-risk indicators and in consequence to adapt the fall risk assessment tool.

Ants in the OCEAN: Modulating Agents with Personality for Planning with Humans.

Ahrndt, S., Aria, A., Fähndrich, J., & Albayrak, S. (2015). In N. Bulling (Ed.), Multi-Agent Systems, 12th European Conference, EUMAS 2014, Prague, Czech Republic, December 18-19, 2014, Revised Selected Papers (pp. 3–18). Springer International Publishing. http://doi.org/10.1007/978-3-319-17130-2_1

Abstract: This work introduces a prototype that demonstrates the idea of using a psychological theory of personality types known as the Five-Factor Model (FFM) in planning for human-agent teamwork scenarios. FFM is integrated into the BDI model of agency leading to variations in the interpretation of inputs, the decision-making process and the generation of outputs. This is demonstrated in a multi-agent simulation, further, it is outlined how these variations can be used for the planning process in collaborative settings.

Self-Explaining Agents

Fähndrich, J., Ahrndt, S., & Albayrak, S. (2013). Self-Explaining Agents. Jurnal Teknologi (Science & Engineering), 63(3), 53–64. http://doi.org/0.11113/jt.v63.1955

Abstract: We advocate Self-Explanation as the foundation for the Self-* properties. Arguing that for system component to have such properties the underlining foundation is a awareness of them selfs and their environment. In the research area of adaptive software, self-* properties have shifted into focus pushing ever more design decisions to a applications runtime. Thus fostering new paradigms for system development like intelligent agents. This work surveys the state of the art methods of self-explanation in software systems and distills a definition of self-explanation.

Towards Self-Explaining Agents

Fähndrich, J., Ahrndt, S., & Albayrak, S. (2013). Towards Self-Explaining Agents. PAAMS, 221 (Chapter 18), 147–154. http://doi.org/10.1007/978-3-319-00563-8_18

Abstract: We advocate Self-Explanation as the foundation for the Self-* properties. Arguing that for system component to have such properties the underlining foundation is a awareness of them selfs and their environment. In the research area of adaptive software, self-* properties have shifted into focus pushing ever more design decisions to a applications runtime. Thus fostering new paradigms for system development like intelligent agents. This work surveys the state of the art methods of self-explanation in software systems and distills a definition of self-explanation.

Preventing Elderly from Falls: The Agent Perspective in EPRs

Ahrndt, S., Fähndrich, J., & Albayrak, S. (2013). In Y. Demazeau, T. Ishida, J. Corchado, & J. Bajo (Eds.), Advances on Practical Applications of Agents and Multi-Agent Systems (Vol. 7879, pp. 1–12). Springer Berlin Heidelberg. http://doi.org/10.1007/978-3-642-38073-0_1

Abstract: This work presents an approach combining multiple electronic patient records (EPR) to a self-learning fall risk assessment tool. We utilised the agentperspective to model the system, to address privacy issues and to evaluate different distributed information fusion and opinion aggregation techniques towards there applicability to the addressed d omain. Each agent represents a single patient negotiating about unknown fall risk influences in order to adapt the fall-risk assessment tool to the population under care. In addition, we will outline the planned real-world case study.

Best First Search Planning of Service Composition Using Incrementally Refined Context-Dependent Heuristics

Fähndrich, J., (2013). Presented at Conference on Multiagent System Technologies (MATES). Springer, Berlin, Heidelberg, https://doi.org/10.1007/978-3-642-40776-5_34

Abstract: In oder to decide if a agent capability is helpful to achieve a goal, modern search algorithms in AI research use heuristics to narrow the search space by indicating which capability is the best to use. Considering the lack of information about pragmatic meaning, creating sound heuristics automatically out of capability descriptions asks too much of modern reasoning algorithms. Most approaches use semantics in oder to enable the reasoner to improve Word-sense disambiguation in their ontology matching tasks. As semantics are meant to be shared, the information is context independent and quite general. I postulate that context-dependent meaning can play an important role in describing the meaning of concepts used, as some meaning might change with the changes in context. The proposed thesis creates context-dependent heuristics by combining expert knowledge with machine learning. The PhD has the goal of structuring descriptions with a concept introduced in linguistics, introducing a description of domain knowledge and contextual information and thereby enable the automatic creation of context-dependent heuristics. Choosing from the many improvement points of agent planning, this work focuses on the improvement of capability descriptions.

Agents vote against Falls: The Agent Perspective in EPRs

Ahrndt, S., Fähndrich, J., & Albayrak, S. (2013). In Y. Demazeau, T. Ishida, J. Corchado, & J. Bajo (Eds.), Advances on Practical Applications of Agents and Multi-Agent Systems (Vol. 7879, pp. 263–266). Springer Berlin Heidelberg. http://doi.org/10.1007/978-3-642-38073-0_23

Abstract: This work presents an approach combining multiple electronic patient records (EPR) to a self-learning fall risk assessment tool. We utilised the agentperspective to model the system, to address privacy issues and to evaluate different distributed information fusion and opinion aggregation techniques towards there applicability to the addressed d omain. Each agent represents a single patient negotiating about unknown fall risk influences in order to adapt the fall-risk assessment tool to the population under care. In addition, we will outline the planned real-world case study.

Exploring Self-Explanation: The System Side

Fähndrich, J. (2012). 10th German Conference on Multiagent System Technologies, 1–2.

Abstract: When it comes to the design time of software applications, unspecified details always leave room for alternatives. Each alternative requiring self-explanation capabilities in order help with the selection. This work subdivide the problem of self-explanation into four subproblems: First of all, we need to answer what is an explanation? In this work explanations are created by adding semantic and contextual information to descriptions (at runtime), which will ease the inference of some reasoner observing the explanation. Secondly, we need to know what kind of information should be contained in a self-explanation? This also implies the question on how much of a language needs to be known, to understand a description in this language. Afterwards, we must accomplish a way to explain semantic information using such a metalanguage and enriching it with contextual information. Hence, this work analyses the way components are described, how these descriptions are created and which methods of inference can be build upon them.

Mining Application Development for Research

Fähndrich, J., Ahrndt, S., & Albayrak, S. (2012). (Vol. 156, pp. 171–178). Presented at the Highlights in Practical Applications of Agents and Multi-Agent Systems. 10th International Conference on Practical Applications of Agents and Multi-Agent Systems, Springer Berlin / Heidelberg. http://doi.org/10.1007/978-3-642-28762-6_21

Abstract: Nowadays, many research institutes are largely dependent on third party funding. This situation leads to practical work or in other words project work which exceeds the research typical proof of concept implementation. As we were tired of seeing a downward trend in the number of accepted application oriented (full) papers in the major agent conference, we conducted a survey to provide evidence for the thesis that researchers can gain relevant benefits from project work for their research work. Hence, in this paper, we present the results of this survey and discuss different scientific questions researchers should ask themselves during project work.

An Agent-based Augmented Reality Demonstrator in the Domestic Energy Domain

Ahrndt, S., Fähndrich, J., & Lützenberger, M. (2012), 225–228. http://doi.org/10.1007/978-3-642-28786-2_25

Abstract: In this work we propose an approach for comfortable and accelerated development of user interfaces for software agents. We apply model-based techniques and emphasise the capability of this technique by describing two user interfaces which are different in nature, but have been developed with the same model. We present the applicability of both user interfaces by means of an agent-based application in the domestic energy domain. As opposed to similar approaches we retain all degrees of freedom for the applied multi-agent framework.

Analyse von Verfahren zur Kombination von Expertenwissen in Form von Wahrscheinlichkeitsverteilungen im Hinblick auf die verteilte lokale Bayes’sche Fusion


Me: "What’s it gona be for the thesis?"
Other Me: "Lets decide that in a group!"
Me: "Oh, that's gona be a problem.... wait a minute...."
Other Me: "OK, challange accepted."

Abstract: Bayes’sche Informationsfusion kann einen hohen Rechenaufwand erzeugen. Zum Zweck einer Verkürzung der Berechnungszeit wird in dieser Arbeit eine verteilte lokale Bayes’sche Informationsfusion betrachtet. Die Größen von Interesse werden durch eine Lokalisierung in Mengen aufgeteilt, die Bereiche von erhöhtem Interesse beinhalten. Auf diesen Mengen kann ein Agentensystem die Fusion verteilt durchführen. Dadurch, dass die Agenten des Agentensystems sich auf diese lokale Menge der Größen von Interesse beschränken, wird die Wahrscheinlichkeit für die Elemente dieser Menge wahrscheinlicher als sie es global gesehen sind. Die Ergebnisse der verteilten Berechnung müssen so zusammengeführt werden, dass möglichst das gleiche Ergebnis wie bei einer nicht verteilten Bayes’schen Informationsfusion entsteht. Dieses Problem ist mit dem einer Konsensfindung in einer Gruppe vergleichbar. Dabei muss aus den A-posteriori-Wahrscheinlichkeitsverteilungen der Gruppenmitglieder, eine Wahrscheinlichkeitsverteilung erzeugt werden, welche die Ground Truth ausreichend gut annähert.
Eine Pooling-Methode ist eine Methode der Entscheidungstheorie. Diese Pooling-Methoden vereinen die Wahrscheinlichkeitsverteilung, welche die Meinungen/Schätzungen der Gruppenmitglieder repräsentieren. Die entsprechende Fachliteratur wurde nach Pooling-Methoden und Möglichkeiten durchsucht, wie diese bewertet werden können. In der Entscheidungstheorie geschieht dies anhand von Eigenschaften, welche die Pooling-Methoden erfüllen können. Dieser Ansatz wurde hier für eine verteilte lokale Bayes’sche Informationsfusion fortgesetzt. Es werden Eigenschaften von Pooling-Methoden auf ihre Relevanz hinsichtlich einer verteilten lokaler Bayes’schen Informationsfusion untersucht. Auf Ba sis dieser Einsichten werden Vor- und Nachteile von Pooling-Methoden, (am Beispiel des Linear Opinion Pools, des Logarithmic Opinion Pools und des Supra Bayes Ansatz) im Kontext von lokaler Bayes’scher Informationsfusion beleuchtet. Somit wird für diese Beispiele durch Analyse und Bewertung der Eigenschaften eine Aussage über deren Eignung für eine verteilte lokale Bayes’sche Informationsfusion abgeleitet.