The Potsdam Answer Set Solving Collection 5.0

Gebser, Martin; Kaminski, Roland; Kaufmann, Benjamin; Lühne, Patrick; Obermeier, Philipp; Ostrowski, Max; Romero, Javier; Schaub, Torsten; Schellhorn, Sebastian; Wanko, Philipp

doi:10.1007/s13218-018-0528-x

Cited by 28 publications

(23 citation statements)

References 9 publications

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“…Our solution uses a (i) declarative language based on the Event Calculus (EC) logic program [31] to represent and reason about the environment descriptions, speculative hypotheses, preservation specifications and potential histories and logs in a uniform way, (ii) an off-the-shelf Boolean constraint solver for logic programs, called clingo [20], to compute potential histories and logs that satisfy or refute hypotheses, and (iii) and a logic-based learner, called XHAIL [41], to synthesise preservation specifications that cover all histories supportive of a hypothesis. Our choice of EC logic program as a language is due to its successful deployment in the context of requirements operationalisation [4,5] and reasoning about evidence in digital investigations [56].…”

Section: Tool Implementationmentioning

confidence: 99%

On evidence preservation requirements for forensic-ready systems

Alrajeh

Pasquale

Nuseibeh

2017

Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering

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Forensic readiness denotes the capability of a system to support digital forensic investigations of potential, known incidents by preserving in advance data that could serve as evidence explaining how an incident occurred. Given the increasing rate at which (potentially criminal) incidents occur, designing software systems that are forensic-ready can facilitate and reduce the costs of digital forensic investigations. However, to date, little or no attention has been given to how forensic-ready software systems can be designed systematically. In this paper we propose to explicitly represent evidence preservation requirements prescribing preservation of the minimal amount of data that would be relevant to a future digital investigation. We formalise evidence preservation requirements and propose an approach for synthesising specifications for systems to meet these requirements. We present our prototype implementationbased on a satisfiability solver and a logic-based learner-which we use to evaluate our approach, applying it to two digital forensic corpora. Our evaluation suggests that our approach preserves relevant data that could support hypotheses of potential incidents. Moreover, it enables significant reduction in the volume of data that would need to be examined during an investigation.

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Section: Tool Implementationmentioning

confidence: 99%

On evidence preservation requirements for forensic-ready systems

Alrajeh

Pasquale

Nuseibeh

2017

Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering

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“…The symbolic knowledge representation is based on Answer Set Programming (Lifschitz 2008), and the system delegates the actual automated reasoning to the answer set solver CLINGO (Gebser et al 2011). The module and the reasoner exchange information through ASP files containing the knowledge base, the queries, and the output of the reasoning process.…”

Section: Robot Task Planningmentioning

confidence: 99%

BWIBots: A platform for bridging the gap between AI and human–robot interaction research

Khandelwal

Zhang

Sinapov

et al. 2017

The International Journal of Robotics Research

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Recent progress in both Artificial Intelligence (AI) and Robotics have enabled the development of general purpose robot platforms that are capable of executing a wide variety of complex, temporally extended service tasks in open environments. This article introduces a novel, custom-designed multi-robot platform for research on AI, robotics, and especially Human-Robot Interaction (HRI) for service robots. Called BWIBots, the robots were designed as a part of the Building-Wide Intelligence (BWI) project at the University of Texas at Austin. The article begins with a description of, and justification for, the hardware and software design decisions underlying the BWIBots, with the aim of informing the design of such platforms in the future. It then proceeds to present an overview of various research contributions that have enabled the BWIBots to better (i) execute action sequences to complete user requests, (ii) efficiently ask questions to resolve user requests, (iii) understand human commands given in natural language, and (iv) understand human intention from afar. The article concludes with a look forward towards future research opportunities and applications enabled by the BWIBot platform.

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“…by a rule in ASP. Then, if the robot sees a package which does not belong to anyone, it can infer (using the ASP solver CLINGO [15]) that the package is suspicious with the commonsense knowledge.…”

Section: A Semantic Reasoningmentioning

confidence: 99%

COACHES: An assistance multi-robot system in public areas

Jeanpierre

Mouaddib

Locchi

et al. 2017

2017 European Conference on Mobile Robots (ECMR)

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Abstract-In this paper, we present a robust system of selfdirected autonomous robots evolving in a complex and public spaces and interacting with people. This system integrates highlevel skills of environment modeling using knowledge-based modeling and reasoning and scene understanding with robust image and video analysis, distributed autonomous decisionmaking using Markov decision process and Petri-Net planning, short-term interacting with humans and robust and safe navigation in overcrowding spaces. This system has been deployed in a variety of public environments such as a shopping mall, a center of congress and in a lab to assist people and visitors. The results are very satisfying showing the effectiveness of the system and going beyond just a simple proof of concepts.

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The Potsdam Answer Set Solving Collection 5.0

Cited by 28 publications

References 9 publications

On evidence preservation requirements for forensic-ready systems

On evidence preservation requirements for forensic-ready systems

BWIBots: A platform for bridging the gap between AI and human–robot interaction research

COACHES: An assistance multi-robot system in public areas

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