56,733 research outputs found
Negotiation in Multi-Agent Systems
In systems composed of multiple autonomous agents, negotiation is a key form of interaction that enables groups of agents to arrive at a mutual agreement regarding some belief, goal or plan, for example. Particularly because the agents are autonomous and cannot be assumed to be benevolent, agents must influence others to convince them to act in certain ways, and negotiation is thus critical for managing such inter-agent dependencies. The process of negotiation may be of many different forms, such as auctions, protocols in the style of the contract net, and argumentation, but it is unclear just how sophisticated the agents or the protocols for interaction must be for successful negotiation in different contexts. All these issues were raised in the panel session on negotiation
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
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