Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Raghavan, Aneesh"'
Autor:
Raghavan, Aneesh, Johansson, Karl H
We consider the problem of identification of safe regions in the environment of an autonomous system. The environment is divided into a finite collections of Voronoi cells, with each cell having a representative, the Voronoi center. The extent to whi
Externí odkaz:
http://arxiv.org/abs/2412.10627
Autor:
Raghavan, Aneesh, Johansson, Karl H.
We consider a collaborative iterative algorithm with two agents and a fusion center for estimation of a real valued function (or ``model") on the set of real numbers. While the data collected by the agents is private, in every iteration of the algori
Externí odkaz:
http://arxiv.org/abs/2407.05136
A given region in 2-D Euclidean space is divided by a unknown linear classifier in to two sets each carrying a label. The objective of an agent with known dynamics traversing the region is to identify the true classifier while paying a control cost a
Externí odkaz:
http://arxiv.org/abs/2403.15687
We consider the problem of estimation of a function by a system consisting of two agents and a fusion center. The two agents collect data comprising of samples of an independent variable and the corresponding value of a dependent variable. The object
Externí odkaz:
http://arxiv.org/abs/2403.07749
We consider the problem of function estimation by a multi-agent system comprising of two agents and a fusion center. Each agent receives data comprising of samples of an independent variable (input) and the corresponding values of the dependent varia
Externí odkaz:
http://arxiv.org/abs/2401.03012
Autor:
Raghavan, Aneesh, Baras, John S.
We consider the binary hypothesis testing problem with two observers. There are two possible states of nature (or hypotheses). Observations collected by the two observers are statistically related to the true state of nature. The knowledge of joint d
Externí odkaz:
http://arxiv.org/abs/2003.11612
Autor:
Raghavan, Aneesh, Baras, John S.
In multi-agent systems, agents observe data, and use them to make inferences and take actions. As a result sensing and control naturally interfere, more so from a real-time perspective. A natural consequence is that in multi-agent systems there are p
Externí odkaz:
http://arxiv.org/abs/2003.11693
Publikováno v:
In IFAC PapersOnLine 2018 51(9):124-129
