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We propose a way to estimate the value function of a convex proximal minimization problem. The scheme constructs a convex set within which the optimizer resides and iteratively refines the set every time that the value function is sampled, namely every tim ...
This work considers a diffusion network responding to streaming data, and studies the problem of identifying the topology of a subnetwork of observable agents by tracking their output measurements. Topology inference from indirect and/or incomplete dataset ...
In reinforcement learning, agents learn by performing actions and observing their outcomes. Sometimes, it is desirable for a human operator to \textit{interrupt} an agent in order to prevent dangerous situations from happening. Yet, as part of their learni ...
We focus on the control of heterogeneous swarms of agents that evolve in a random environment. Control is achieved by introducing special agents: leader and infiltrated (shill) agents. A refined distinction is made between hidden and apparent controlling a ...
The collective dynamic behavior of large groups of interacting autonomous agents (swarms) have inspired much research in both fundamental and engineering sciences. It is now widely acknowledged that the intrinsic nonlinearities due to mutual interactions c ...
In this paper we demonstrate how agent-based modelling can be used to understand the emergence of a new infrastructure system, more specifically, a biogas infrastructure in the Netherlands. The innovative element in our modelling approach is the use of MAI ...
This article reports on the calibration and analysis of a fully disaggregate (agent-based) transport simulation for the metropolitan area of Zurich. The agent-based simulation goes beyond traditional transport models in that it equilibrates not only route ...
We consider the problem of dictionary learning over large scale models, where the model parameters are distributed over a multi-agent network. We demonstrate that the dual optimization problem for inference is better conditioned than the primal problem and ...
We present a methodology for the automatic verification of multi-agent systems against temporal-epistemic specifications derived from higher-level languages defined over convergent equational theories. We introduce a modality called rewriting knowledge that o ...
Multi agent system is a system consist of multiple interacting agents. These systems tend to select the best solution for their problems. They can be used in different tasks which are hard for an individual or even a complex system to do. One of the most c ...
