Multi-agent Confidential Abductive Reasoning

In the context of multi-agent hypothetical reasoning, agents typically have partial knowledge about their environments, and the union of such knowledge is still incomplete to represent the whole world. Thus, given a global query they collaborate with each other to make correct inferences and hypothesis, whilst maintaining global constraints. Most collaborative reasoning systems operate on the assumption that agents can share or communicate any information they have. However, in application domains like multi-agent systems for healthcare or distributed software agents for security policies in coalition networks, confidentiality of knowledge is an additional primary concern. These agents are required to collaborately compute consistent answers for a query whilst preserving their own private information. This paper addresses this issue showing how this dichotomy between "open communication" in collaborative reasoning and protection of confidentiality can be accommodated. We present a general-purpose distributed abductive logic programming system for multi-agent hypothetical reasoning with confidentiality. Specifically, the system computes consistent conditional answers for a query over a set of distributed normal logic programs with possibly unbound domains and arithmetic constraints, preserving the private information within the logic programs. A case study on security policy analysis in distributed coalition networks is described, as an example of many applications of this system

Speculative orientation and tracking system

The current progresses at the intersection of computer science and health care have the potential of greatly improving the living conditions of people with disabilities by removing obstacles that impair the normal unfolding of their everyday lives. Assistive technologies, as an application of scientific knowledge, aim to help users with their diminished capacities and, usually, imply a small adaptation from individuals so that they can use the devices that convey assistive functionalities. One of the most commonly diminished capabilities is that of spatial orientation. This is mirrored by several research works whose goal is to help human beings to travel between locations. Once set up, most of the systems featured in these research works requires changes in the configurations to be made manually in order to achieve a better adjustment to the user. In order to overcome this drawback, the work presented herein features a framework of Speculative Computation to set up the computation of the next step of a user using default values. The consequence of the application of the framework is a faster reaction to user stimuli, which may result in issuing warnings when he is likely to choose the wrong direction.This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT Fundac¸ao para a Ci ˜ encia e a Tecnologia (Portuguese Foundation for Science and ˆ Technology) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012). The work of Joao Ramos is supported by a doctoral grant by FCT - Fundac¸ ˜ ao para a Ci ˜ encia e a ˆ Tecnologia (Portuguese Foundation for Science and Technology) SFRH/BD/89530/2012. The work of Tiago Oliveira is also supported by the FCT grant with the reference SFRH/BD/85291/- 2012.info:eu-repo/semantics/publishedVersio

A dynamic default revision mechanism for speculative computation

In this work a default revision mechanism is introduced into Speculative Computation to manage incomplete information. The default revision is supported by a method for the generation of default constraints based on Bayesian Networks. The method enables the generation of an initial set of defaults which is used to produce the most likely scenarios during the computation, represented by active processes. As facts arrive, the Bayesian Network is used to derive new defaults. The objective with such a new dynamic mechanism is to keep the active processes coherent with arrived facts. This is achieved by changing the initial set of default constraints during the reasoning process in Speculative Computation. A practical example in clinical decision support is described.info:eu-repo/semantics/publishedVersio

Multi-Agent Systems

This Special Issue ""Multi-Agent Systems"" gathers original research articles reporting results on the steadily growing area of agent-oriented computing and multi-agent systems technologies. After more than 20 years of academic research on multi-agent systems (MASs), in fact, agent-oriented models and technologies have been promoted as the most suitable candidates for the design and development of distributed and intelligent applications in complex and dynamic environments. With respect to both their quality and range, the papers in this Special Issue already represent a meaningful sample of the most recent advancements in the field of agent-oriented models and technologies. In particular, the 17 contributions cover agent-based modeling and simulation, situated multi-agent systems, socio-technical multi-agent systems, and semantic technologies applied to multi-agent systems. In fact, it is surprising to witness how such a limited portion of MAS research already highlights the most relevant usage of agent-based models and technologies, as well as their most appreciated characteristics. We are thus confident that the readers of Applied Sciences will be able to appreciate the growing role that MASs will play in the design and development of the next generation of complex intelligent systems. This Special Issue has been converted into a yearly series, for which a new call for papers is already available at the Applied Sciences journal’s website: https://www.mdpi.com/journal/applsci/special_issues/Multi-Agent_Systems_2019