A decentralized, agent-based approach to road pricing is shown in [9], where the authors compare the performance of autonomous links and centralized control on capacity expansion of a highway network.
This paper addresses this problem by presenting ATALK, a novel decentralized agent middleware that fulfills the above requirements.
Each vehicle is provided with a decentralized agent-based robust nonlinear model predictive controller and a set of nonlinear guidance laws for trajectory tracking.
We present in this paper a novel load balancing and rescheduling approach based on the concept of the Sandpile cellular automaton: a decentralized multi-agent system working in a critical state at the edge of chaos.
Agent-based modeling is a computational method that enables researchers to create, analyze, and experiment with models composed of decentralized agents that interact with each other and within an environment according to localized knowledge[6].
Herein, the authors present fundamental properties required by a decentralized microgrid multi-agent system (MAS), define agent capabilities that support resilient operations, and discuss aspects of the microgrid MAS necessary to smoothly transition between system states.
We characterize in this paper the weighted averages that can be evaluated in a decentralized way by agents communicating over a directed graph.
The original large-scale power system is firstly divided into several small-scale subsystems, in which each subsystem is regarded as an agent, such that a decentralized OCECF can be achieved via a Nash game among all the agents.
This paper addresses the design of a decentralized safety controller for two agents, subject to communication delay and imperfect measurements.
Thus, it is critical to effectively coordinate the harvesting operations of the agents in a decentralized and lightweight way.
This is reasonable if we assume that capital allocation and employment decisions were made in a decentralized way by profit-maximizing agents.
