4,172 research outputs found
Multi-agent Systems with Compasses
This paper investigates agreement protocols over cooperative and
cooperative--antagonistic multi-agent networks with coupled continuous-time
nonlinear dynamics. To guarantee convergence for such systems, it is common in
the literature to assume that the vector field of each agent is pointing inside
the convex hull formed by the states of the agent and its neighbors, given that
the relative states between each agent and its neighbors are available. This
convexity condition is relaxed in this paper, as we show that it is enough that
the vector field belongs to a strict tangent cone based on a local supporting
hyperrectangle. The new condition has the natural physical interpretation of
requiring shared reference directions in addition to the available local
relative states. Such shared reference directions can be further interpreted as
if each agent holds a magnetic compass indicating the orientations of a global
frame. It is proven that the cooperative multi-agent system achieves
exponential state agreement if and only if the time-varying interaction graph
is uniformly jointly quasi-strongly connected. Cooperative--antagonistic
multi-agent systems are also considered. For these systems, the relation has a
negative sign for arcs corresponding to antagonistic interactions. State
agreement may not be achieved, but instead it is shown that all the agents'
states asymptotically converge, and their limits agree componentwise in
absolute values if and in general only if the time-varying interaction graph is
uniformly jointly strongly connected.Comment: SIAM Journal on Control and Optimization, In pres
On Steering Swarms
The main contribution of this paper is a novel method allowing an external
observer/controller to steer and guide swarms of identical and
indistinguishable agents, in spite of the agents' lack of information on
absolute location and orientation. Importantly, this is done via simple global
broadcast signals, based on the observed average swarm location, with no need
to send control signals to any specific agent in the swarm
Rendezvous of Two Robots with Constant Memory
We study the impact that persistent memory has on the classical rendezvous
problem of two mobile computational entities, called robots, in the plane. It
is well known that, without additional assumptions, rendezvous is impossible if
the entities are oblivious (i.e., have no persistent memory) even if the system
is semi-synchronous (SSynch). It has been recently shown that rendezvous is
possible even if the system is asynchronous (ASynch) if each robot is endowed
with O(1) bits of persistent memory, can transmit O(1) bits in each cycle, and
can remember (i.e., can persistently store) the last received transmission.
This setting is overly powerful.
In this paper we weaken that setting in two different ways: (1) by
maintaining the O(1) bits of persistent memory but removing the communication
capabilities; and (2) by maintaining the O(1) transmission capability and the
ability to remember the last received transmission, but removing the ability of
an agent to remember its previous activities. We call the former setting
finite-state (FState) and the latter finite-communication (FComm). Note that,
even though its use is very different, in both settings, the amount of
persistent memory of a robot is constant.
We investigate the rendezvous problem in these two weaker settings. We model
both settings as a system of robots endowed with visible lights: in FState, a
robot can only see its own light, while in FComm a robot can only see the other
robot's light. We prove, among other things, that finite-state robots can
rendezvous in SSynch, and that finite-communication robots are able to
rendezvous even in ASynch. All proofs are constructive: in each setting, we
present a protocol that allows the two robots to rendezvous in finite time.Comment: 18 pages, 3 figure
Managing healthcare workflows in a multi-agent system environment
Whilst Multi-Agent System (MAS) architectures appear to offer a more flexible model for designers and developers of complex, collaborative information systems, implementing real-world business processes that can be delegated to autonomous agents is still a relatively difficult task. Although a range of agent tools and toolkits exist, there still
remains the need to move the creation of models nearer to code generation, in order that the development path be more rigorous and repeatable. In particular, it is essential that complex organisational
process workflows are captured and expressed in a way that MAS can successfully interpret. Using a complex social care system as an exemplar, we describe a technique whereby a business process is
captured, expressed, verified and specified in a suitable format for a healthcare MAS.</p
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