132,221 research outputs found
Mixed Initiative Systems for Human-Swarm Interaction: Opportunities and Challenges
Human-swarm interaction (HSI) involves a number of human factors impacting
human behaviour throughout the interaction. As the technologies used within HSI
advance, it is more tempting to increase the level of swarm autonomy within the
interaction to reduce the workload on humans. Yet, the prospective negative
effects of high levels of autonomy on human situational awareness can hinder
this process. Flexible autonomy aims at trading-off these effects by changing
the level of autonomy within the interaction when required; with
mixed-initiatives combining human preferences and automation's recommendations
to select an appropriate level of autonomy at a certain point of time. However,
the effective implementation of mixed-initiative systems raises fundamental
questions on how to combine human preferences and automation recommendations,
how to realise the selected level of autonomy, and what the future impacts on
the cognitive states of a human are. We explore open challenges that hamper the
process of developing effective flexible autonomy. We then highlight the
potential benefits of using system modelling techniques in HSI by illustrating
how they provide HSI designers with an opportunity to evaluate different
strategies for assessing the state of the mission and for adapting the level of
autonomy within the interaction to maximise mission success metrics.Comment: Author version, accepted at the 2018 IEEE Annual Systems Modelling
Conference, Canberra, Australi
Consciosusness in Cognitive Architectures. A Principled Analysis of RCS, Soar and ACT-R
This report analyses the aplicability of the principles of consciousness developed in the ASys project to three of the most relevant cognitive architectures. This is done in relation to their aplicability to build integrated control systems and studying their support for general mechanisms of real-time consciousness.\ud
To analyse these architectures the ASys Framework is employed. This is a conceptual framework based on an extension for cognitive autonomous systems of the General Systems Theory (GST).\ud
A general qualitative evaluation criteria for cognitive architectures is established based upon: a) requirements for a cognitive architecture, b) the theoretical framework based on the GST and c) core design principles for integrated cognitive conscious control systems
Intelligent Agents for Disaster Management
ALADDIN [1] is a multi-disciplinary project that is developing novel techniques, architectures, and mechanisms for multi-agent systems in uncertain and dynamic environments. The application focus of the project is disaster management. Research within a number of themes is being pursued and this is considering different aspects of the interaction between autonomous agents and the decentralised system architectures that support those interactions. The aim of the research is to contribute to building more robust multi-agent systems for future applications in disaster management and other similar domains
Teaching about Madrid: A Collaborative Agents-Based Distributed Learning Course
Interactive art courses require a huge amount of computational resources to be running on real time. These computational resources are even bigger if the course has been designed as a Virtual Environment with which students can interact. In this paper, we present an initiative that has been develop in a close collaboration between two Spanish Universities: Universidad PolitĂ©cnica de Madrid and Universidad Rey Juan Carlos with the aim of join two previous research project: a Collaborative Awareness Model for Task-Balancing-Delivery (CAMT) in clusters and the âTeaching about Madridâ course, which provides a cultural interactive background of the capital of Spain
Using acoustic sensor technologies to create a more terrain capable unmanned ground vehicle
Unmanned Ground Vehicleâs (UGV) have to cope with the most complex range of dynamic and variable obstacles and therefore need to be highly intelligent in order to cope with navigating in such a cluttered environment. When traversing over different terrains (whether it is a UGV or a commercial manned vehicle) different drive styles and configuration settings need to be selected in order to travel successfully over each terrain type. These settings are usually selected by a human operator in manned systems on what they assume the ground conditions to be, but how can an autonomous UGV âsenseâ these changes in terrain or ground conditions? This paper will investigate noncontact acoustic sensor technologies and how they can be used to detect different terrain types by listening to the interaction between the wheel and the terrain. The results can then be used to create a terrain classification list for the system so in future missions it can use the sensor technology to identify the terrain type it is trying to traverse, which creating a more autonomous and terrain capable vehicle. The technology would also benefit commercial driver assistive technologie
Responsible Autonomy
As intelligent systems are increasingly making decisions that directly affect
society, perhaps the most important upcoming research direction in AI is to
rethink the ethical implications of their actions. Means are needed to
integrate moral, societal and legal values with technological developments in
AI, both during the design process as well as part of the deliberation
algorithms employed by these systems. In this paper, we describe leading ethics
theories and propose alternative ways to ensure ethical behavior by artificial
systems. Given that ethics are dependent on the socio-cultural context and are
often only implicit in deliberation processes, methodologies are needed to
elicit the values held by designers and stakeholders, and to make these
explicit leading to better understanding and trust on artificial autonomous
systems.Comment: IJCAI2017 (International Joint Conference on Artificial Intelligence
Semi-autonomous, context-aware, agent using behaviour modelling and reputation systems to authorize data operation in the Internet of Things
In this paper we address the issue of gathering the "informed consent" of an
end user in the Internet of Things. We start by evaluating the legal importance
and some of the problems linked with this notion of informed consent in the
specific context of the Internet of Things. From this assessment we propose an
approach based on a semi-autonomous, rule based agent that centralize all
authorization decisions on the personal data of a user and that is able to take
decision on his behalf. We complete this initial agent by integrating
context-awareness, behavior modeling and community based reputation system in
the algorithm of the agent. The resulting system is a "smart" application, the
"privacy butler" that can handle data operations on behalf of the end-user
while keeping the user in control. We finally discuss some of the potential
problems and improvements of the system.Comment: This work is currently supported by the BUTLER Project co-financed
under the 7th framework program of the European Commission. published in
Internet of Things (WF-IoT), 2014 IEEE World Forum, 6-8 March 2014, Seoul,
P411-416, DOI: 10.1109/WF-IoT.2014.6803201, INSPEC: 1425565
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Metacognitive knowledge, metacognitive strategies, and CALL
CALL Research Perspectives creates a foundation for the study and practice of computer-assisted language learning and provides an overview of ways to conceptualize and to conduct research in CALL. Its core assumptions are that all approaches to research have a place, and that researchers, teachers, and students all have a role to play in the study of computer-enhanced language learning.
This is not a how-to-do-research text. Written by top researchers in the field, it offers an open-ended view of what educators need to know and be able to do to answer questions that they have. It is intended to be easy to read, to provide resources for readers to explore the ideas further, and to be non-prescriptive in presenting suggestions for CALL research. The text explores problems with current CALL research and suggests ways that teachers and other researchers can avoid such problems; presents both commonly known and less explored theories that provide a foundation for CALL and language research; and addresses other issues and ideas that affect research outcomes
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