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Philipp Kraus currently works at the Department of Computer Science, Technische Universität Clausthal. Philipp does research in Artificial Intelligence, Algorithms and Computing in Mathematics, Natural Science, Engineering and Medicine. Their current projects are 'LightJason: Concurrent high-scalable BDI multi-agent framework' and 'SocialCars: Cooperative (De-)Centralized Traffic Management'.
Current work on delay management in railway networks has – to the best of our knowledge – largely ignored the impact of passengers’ behavior on train delays. This paper describes ongoing work aiming to explore this topic. We propose a hybrid agent-based architecture combining a macroscopic railway network simulation with a microscopic simulation of...
Modeling and simulation of pedestrian behavior is used in applications such as planning large buildings, disaster management, or urban planning. Realistically simulating pedestrian behavior is challenging, due to the complexity of individual behavior as well as the complexity of interactions of pedestrians with each other and with the environment....
Current BDI agent frameworks often lack necessary modularity, scalability and are hard to integrate with non-agent applications. This paper reports ongoing research on LightJason, a multi-agent BDI framework based on AgentSpeak(L), fine-tuned to concurrent plan execution in a distributed framework; LightJason aims at efficient and scalable integrat...
Using purely agent-based platforms for any kind of simulation requires to address the following challenges: 1) scalability; 2) efficient memory management; 3) modelling. While dedicated professional simulation tools usually provide rich domain libraries and advanced visualisation techniques, and support the simulation of large scenarios, they do no...
Using purely agent-based platforms for any kind of simulation requires to address the following challenges: 1 scalability; 2 efficient memory management; 3 modelling. While dedicated professional simulation tools usually provide rich domain libraries and advanced visualisation techniques, and support the simulation of large scenarios, they do not a...
Using purely agent-based platforms for any kind of simulation requires to address the following challenges: (1) scalability (efficient scheduling of agent cycles is difficult), (2) efficient memory management (when and which data should be fetched, cached, or written to/from disk), and (3) modelling (no generally accepted meta-models exist: what ar...
The project contains the development / research of a new generation of multi-agent system frameworks with concurrent (high) scalable cloud- and parallel computing structure Website: http://lightjason.org
The overall objective of the SocialCars Research Training Group is to research new methods and applications of decentralized, cooperative traffic management, that are en-abled by new technological trends and developments such as Car-to-X communication. SocialCars focuses on the interplay of centralized management in the sense of classical traffic control, and decentralized management in the sense of the local goals of individual traffic participants. In order to comprehensively study this interplay while considering both the requirements of traffic participants and the constraints of the urban environment, we propose six fields of research, in which we investigate novel and interdisciplinary research questions. In these fields of research, we study problems related to behavioural aspects of traffic participants, societal objectives, technical and algorithmic foundations of communica-tion, interaction, and dynamic geo-information, as well as models and methods of coopera-tive, (de)centralized traffic management. We research solutions to these problems that will enable us to realistically describe dynamic cooperative traffic systems, and to evolve and optimize such systems in accordance with societal objectives. For details see http://www.socialcars.org/