Zobrazeno 1 - 10
of 372
pro vyhledávání: '"Adámy, A."'
A major challenge in the development of Model Predictive Control (MPC)-based energy management systems (EMSs) for buildings is the availability of an accurate model. One approach to address this is to augment an existing gray-box model with data-driv
Externí odkaz:
http://arxiv.org/abs/2407.13308
Publikováno v:
Transactions on Intelligent Vehicles (TIV 2022)
The survival analysis of driving trajectories allows for holistic evaluations of car-related risks caused by collisions or curvy roads. This analysis has advantages over common Time-To-X indicators, such as its predictive and probabilistic nature. Ho
Externí odkaz:
http://arxiv.org/abs/2303.08458
Publikováno v:
In Applied Energy 15 October 2024 372
We are concerned with a distributed approach to solve multi-cluster games arising in multi-agent systems. In such games, agents are separated into distinct clusters. The agents belonging to the same cluster cooperate with each other to achieve a comm
Externí odkaz:
http://arxiv.org/abs/2202.12124
When cooperating with a human, a robot should not only care about its environment and task but also develop an understanding of the partner's reasoning. To support its human partner in complex tasks, the robot can share information that it knows. How
Externí odkaz:
http://arxiv.org/abs/2109.01355
We study a distributed approach for seeking a Nash equilibrium in $n$-cluster games with strictly monotone mappings. Each player within each cluster has access to the current value of her own smooth local cost function estimated by a zero-order oracl
Externí odkaz:
http://arxiv.org/abs/2107.12648
We are concerned with finding Nash Equilibria in agent-based multi-cluster games, where agents are separated into distinct clusters. While the agents inside each cluster collaborate to achieve a common goal, the clusters are considered to be virtual
Externí odkaz:
http://arxiv.org/abs/2102.09406
Domain Adaptation (DA) is a highly relevant research topic when it comes to image classification with deep neural networks. Combining multiple source domains in a sophisticated way to optimize a classification model can improve the generalization to
Externí odkaz:
http://arxiv.org/abs/2010.07783
We discovered a deficiency in Algorithm 1 and Theorem 3 of [1]. The algorithm called CEMA aims to solve an energy management problem distributively. However, by means of a counter example, we show that Theorem 2 and 3 of [1] contradict each other in
Externí odkaz:
http://arxiv.org/abs/2009.08758
We propose a novel algorithm for solving convex, constrained and distributed optimization problems defined on multi-agent-networks, where each agent has exclusive access to a part of the global objective function. The agents are able to exchange info
Externí odkaz:
http://arxiv.org/abs/2004.02854