87,311 research outputs found
Field-based Coordination with the Share Operator
Field-based coordination has been proposed as a model for coordinating
collective adaptive systems, promoting a view of distributed computations as
functions manipulating data structures spread over space and evolving over
time, called computational fields. The field calculus is a formal foundation
for field computations, providing specific constructs for evolution (time) and
neighbor interaction (space), which are handled by separate operators (called
rep and nbr, respectively). This approach, however, intrinsically limits the
speed of information propagation that can be achieved by their combined use. In
this paper, we propose a new field-based coordination operator called share,
which captures the space-time nature of field computations in a single operator
that declaratively achieves: (i) observation of neighbors' values; (ii)
reduction to a single local value; and (iii) update and converse sharing to
neighbors of a local variable. We show that for an important class of
self-stabilising computations, share can replace all occurrences of rep and nbr
constructs. In addition to conceptual economy, use of the share operator also
allows many prior field calculus algorithms to be greatly accelerated, which we
validate empirically with simulations of frequently used network propagation
and collection algorithms
Artificial Intelligence and Systems Theory: Applied to Cooperative Robots
This paper describes an approach to the design of a population of cooperative
robots based on concepts borrowed from Systems Theory and Artificial
Intelligence. The research has been developed under the SocRob project, carried
out by the Intelligent Systems Laboratory at the Institute for Systems and
Robotics - Instituto Superior Tecnico (ISR/IST) in Lisbon. The acronym of the
project stands both for "Society of Robots" and "Soccer Robots", the case study
where we are testing our population of robots. Designing soccer robots is a
very challenging problem, where the robots must act not only to shoot a ball
towards the goal, but also to detect and avoid static (walls, stopped robots)
and dynamic (moving robots) obstacles. Furthermore, they must cooperate to
defeat an opposing team. Our past and current research in soccer robotics
includes cooperative sensor fusion for world modeling, object recognition and
tracking, robot navigation, multi-robot distributed task planning and
coordination, including cooperative reinforcement learning in cooperative and
adversarial environments, and behavior-based architectures for real time task
execution of cooperating robot teams
Teams organization and performance analysis in autonomous human-robot teams
This paper proposes a theory of human control of robot teams based on considering how people coordinate across different task allocations. Our current work focuses on domains such as foraging in which robots perform largely independent tasks. The present study addresses the interaction between automation and organization of human teams in controlling large robot teams performing an Urban Search and Rescue (USAR) task. We identify three subtasks: perceptual search-visual search for victims, assistance-teleoperation to assist robot, and navigation-path planning and coordination. For the studies reported here, navigation was selected for automation because it involves weak dependencies among robots making it more complex and because it was shown in an earlier experiment to be the most difficult. This paper reports an extended analysis of the two conditions from a larger four condition study. In these two "shared pool" conditions Twenty four simulated robots were controlled by teams of 2 participants. Sixty paid participants (30 teams) were recruited to perform the shared pool tasks in which participants shared control of the 24 UGVs and viewed the same screens. Groups in the manual control condition issued waypoints to navigate their robots. In the autonomy condition robots generated their own waypoints using distributed path planning. We identify three self-organizing team strategies in the shared pool condition: joint control operators share full authority over robots, mixed control in which one operator takes primary control while the other acts as an assistant, and split control in which operators divide the robots with each controlling a sub-team. Automating path planning improved system performance. Effects of team organization favored operator teams who shared authority for the pool of robots. © 2010 ACM
European Communications at the Crossroads. Report of the CEPS Working Party on electronic communications. CEPS Task Force Reports No. 39, 1 October 2001
Community institutions are now busy with the second readings of the proposals for a new regime for regulating the European Communications Industry. While many aspects of the proposed new regulatory arrangements are widely accepted, a number of key choices still have to be made. The regulation of European communications is therefore at a crossroads. This CEPS Working Party Report considers the key choices that lie ahead, with the aim of providing the institutions with some fresh input from well placed observers
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