Experimenting with robotic intra-logistics domains

AbstractWe introduce theasprilo1framework to facilitate experimental studies of approaches addressing complex dynamic applications. For this purpose, we have chosen the domain of robotic intra-logistics. This domain is not only highly relevant in the context of today's fourth industrial revolution but it moreover combines a multitude of challenging issues within a single uniform framework. This includes multi-agent planning, reasoning about action, change, resources, strategies, etc. In return,aspriloallows users to study alternative solutions as regards effectiveness and scalability. Althoughasprilorelies on Answer Set Programming and Python, it is readily usable by any system complying with its fact-oriented interface format. This makes it attractive for benchmarking and teaching well beyond logic programming. More precisely,aspriloconsists of a versatile benchmark generator, solution checker and visualizer as well as a bunch of reference encodings featuring various ASP techniques. Importantly, the visualizer's animation capabilities are indispensable for complex scenarios like intra-logistics in order to inspect valid as well as invalid solution candidates. Also, it allows for graphically editing benchmark layouts that can be used as a basis for generating benchmark suites.

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A Generic Self-Evolving Multi-Agent Defense Approach Against Cyber Attacks

Cyber Law, Privacy, and Security ◽

10.4018/978-1-5225-8897-9.ch011 ◽

2019 ◽

pp. 210-226

Author(s):

Stephen Mugisha Akandwanaho ◽

Irene Govender

Keyword(s):

Industrial Revolution ◽

Cyber Attacks ◽

Multiple Agents ◽

Low Level ◽

Single Interface ◽

Cyber Threats ◽

Fourth Industrial Revolution ◽

Multi Agent

A generic self-evolving multi-agent approach is proposed in this chapter. Most of the existing security approaches are custom designed for specific threats and attacks. However, the fusion of technologies and systems in the fourth industrial revolution and therefore the nature of its current cyber environment increasingly attracts multiple cyber threats in a single interface. In order to solve this problem, a generic self-evolving multi-agent approach is proposed. Multiple agents interact with each other in light of their reactions towards the environment and its inherent changes. Information from individual agents is collected and integrated to form the abstract compartment of the structure. The important aspects are analyzed including demonstrating how the abstract domain can be obtained from the custom interactions at the low-level domain of the proposed approach. The analysis explores the existing works in the area and how they have been advanced in the fourth industrial revolution.

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A Generic Self-Evolving Multi-Agent Defense Approach Against Cyber Attacks

Handbook of Research on Information and Cyber Security in the Fourth Industrial Revolution - Advances in Information Security, Privacy, and Ethics ◽

10.4018/978-1-5225-4763-1.ch006 ◽

2018 ◽

pp. 165-181

Author(s):

Stephen Mugisha Akandwanaho ◽

Irene Govender

Keyword(s):

Industrial Revolution ◽

Cyber Attacks ◽

Multiple Agents ◽

Low Level ◽

Single Interface ◽

Cyber Threats ◽

Fourth Industrial Revolution ◽

Multi Agent

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Modeling and development of a multi-agent space for the secondary school

Informatics and Education ◽

10.32517/0234-0453-2020-35-4-53-62 ◽

2020 ◽

pp. 53-62

Author(s):

I. K. Krasteva ◽

T. A. Glushkova ◽

S. N. Stoyanov

Keyword(s):

Secondary School ◽

Lifelong Learning ◽

Industrial Revolution ◽

Educational Systems ◽

Fourth Industrial Revolution ◽

Agent Learning ◽

Multi Agent ◽

Personal Assistants ◽

The University

One of the guiding principles of the Fourth Industrial Revolution is the need for lifelong learning. This determines the growing role of intelligent educational systems to provide the necessary learning resources and services to users at any time and any place. This article presents the modeling and development of an intelligent multi-agent learning environment for the secondary school, developed by a team of the DeLC laboratory at the University of Plovdiv “Paisii Hilendarski”, Bulgaria. The learners are placed at the focus of the environment by personal assistants supporting work with the environment.

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