A Generic Agent Organisation Framework For Autonomic Systems

Autonomic computing is being advocated as a tool for managing large, complex computing systems. Specifically, self-organisation provides a suitable approach for developing such autonomic systems by incorporating self-management and adaptation properties into large-scale distributed systems. To aid in this development, this paper details a generic problem-solving agent organisation framework that can act as a modelling and simulation platform for autonomic systems. Our framework describes a set of service-providing agents accomplishing tasks through social interactions in dynamically changing organisations. We particularly focus on the organisational structure as it can be used as the basis for the design, development and evaluation of generic algorithms for self-organisation and other approaches towards autonomic systems

Correlation between permanent tooth eruption pattern and the predominance of the motor function laterality

Objectives: To asses whether dental eruption order can play a role in the early diagnosis of crossed laterality. Study Design: Dental eruption pattern along with eye, ear, hand and foot lateralism were examined on 131 chil - dren between 6 to 8 years old from public schools from a multietnic population area of Barcelona city. Statistic methods (Statgraphics Plus 5.1 program) were used to evaluate data recollected. Results: Only foot and dentition lateralities behave as independent variables regarding hand laterality. So dental eruption laterality (along with the foot one) would be one of the parameters more related to hand laterality given that dentition variable relationship is greater that the foot one. This suggests that tooth eruption could be more clinically relevant. Crossed laterality hand-foot is significantly more predominant in men (13%) than in women (1,6%). Meanwhile, the relationship between hand and dentition didn't show any influence of sex. Conclusions: Dental eruption order, can be used as a good parameter in the determination of the patient's laterality

A Hierarchical Framework for Collaborative Artificial Intelligence

We propose a hierarchical framework for collaborative intelligent systems. This framework organizes research challenges based on the nature of the collaborative activity and the information that must be shared, with each level building on capabilities provided by lower levels. We review research paradigms at each level, with a description of classical engineering-based approaches and modern alternatives based on machine learning, illustrated with a running example using a hypothetical personal service robot. We discuss cross-cutting issues that occur at all levels, focusing on the problem of communicating and sharing comprehension, the role of explanation and the social nature of collaboration. We conclude with a summary of research challenges and a discussion of the potential for economic and societal impact provided by technologies that enhance human abilities and empower people and society through collaboration with intelligent systems

Building collaboration in multi-agent systems using reinforcement learning

© Springer Nature Switzerland AG 2018. This paper presents a proof-of concept study for demonstrating the viability of building collaboration among multiple agents through standard Q learning algorithm embedded in particle swarm optimisation. Collaboration is formulated to be achieved among the agents via competition, where the agents are expected to balance their action in such a way that none of them drifts away of the team and none intervene any fellow neighbours territory, either. Particles are devised with Q learning for self training to learn how to act as members of a swarm and how to produce collaborative/collective behaviours. The produced experimental results are supportive to the proposed idea suggesting that a substantive collaboration can be build via proposed learning algorithm

PrIMe: A Software Engineering Methodology for Developing Provenance-Aware Applications

Provenance is a concept often used in the Art world to refer to the documented history of an artifact, providing information about the artifact’s lineage and authenticity. Provenance-aware applications similarly allow their users to have confidence about the data they produce, and can enable users to make judgements relating to notions of trust, accountability, validation, replication and compliance of their data. PrIMe is a software engineering methodology for adapting applications to enable them to interact with a provenance middleware layer, thereby making them provenance-aware. Such applications allow users to answer questions about provenance use cases, which are descriptions of scenarios in which a user interacts with a system by performing particular functions on that system. In order to illustrate how PrIMe can make applications provenance-aware, an Organ Transplant Management example application is used

Organizing Multiagent Systems

Despite all the research done in the last years on the development of methodologies for designing MAS, there is no methodology suitable for the specification and design of MAS in complex domains where both the agent view and the organizational view can be modelled. Current multi-agent approaches either take a centralist, static approach to organizational design or take an emergent view in which agent interactions are not pre determined, thus making it impossible to make any predictions on the behavior of the whole systems. Most of them also lack a model of the norms in the environment that should rule the (emergent) behavior of the agent society as a whole and/or the actions of individuals. In this paper, we propose a framework for modelling agent organizations, Omni , that allows the balance of global organizational requirements with the autonomy of individual agents. It specifie

The Provenance of Electronic Data

In the study of fine art, provenance refers to the documented history of some art object. Given that documented history, the object attains an authority that allows scholars to appreciate its importance with respect to other works, whereas, in the absence of such history, the object may be treated with some skepticism. Our IT landscape is evolving as illustrated by applications that are open, composed dynamically, and that discover results and services on the fly. Against this challenging background, it is crucial for users to be able to have confidence in the results produced by such applications. If the provenance of data produced by computer systems could be determined as it can for some works of art, then users, in their daily applications, would be able to interpret and judge the quality of data better. We introduce a provenance lifecycle and advocate an open approach based on two key principles to support a notion of provenance in computer systems: documentation of execution and user-tailored provenance queries