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pro vyhledávání: '"Paris Pennesi"'
A Distributed Actor-Critic Algorithm and Applications to Mobile Sensor Network Coordination Problems
Autor:
Ioannis Ch. Paschalidis, Paris Pennesi
Publikováno v:
IEEE Transactions on Automatic Control. 55:492-497
We introduce and establish the convergence of a distributed actor-critic method that orchestrates the coordination of multiple agents solving a general class of a Markov decision problem. The method leverages the centralized single-agent actor-critic
Autor:
Paris Pennesi, Giuseppe Conte
Publikováno v:
IEEE Transactions on Automatic Control. 55:279-283
In this technical note we consider the multi-agent rendezvous problem and we state new sufficient conditions for characterizing the control policies that assure rendezvous. Our condition are less restrictive than those presented until now in the lite
We present a Hawkes-model approach to the foreign exchange market in which the high-frequency price dynamics is affected by a self-exciting mechanism and an exogenous component, generated by the pre-announced arrival of macroeconomic news. By focusin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b5331317ac12deed0c044d067cc1f75
http://hdl.handle.net/11585/597103
http://hdl.handle.net/11585/597103
Publikováno v:
Information Technology in the Service Economy: Challenges and Possibilities for the 21st Century ISBN: 9780387097671
Information Technology in the Service Economy
Information Technology in the Service Economy
In this paper, we propose a case study approach to examine and assess the information required to underpin services for particular industrial service offerings. The focus of this paper is on the means by which service information requirements may be
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c0caef37807860ba2ece181742321c6
https://doi.org/10.1007/978-0-387-09768-8_34
https://doi.org/10.1007/978-0-387-09768-8_34
Autor:
Paris Pennesi, Ioannis Ch. Paschalidis
Publikováno v:
CDC
Multi-robots systems exploiting sensor network capabilities can be successfully employed to cope with several tasks, including coverage, surveillance, target tracking, and foraging, in partially known environments subject to dynamical changes. In thi
Autor:
null Paris Pennesi
Publikováno v:
2006 14th Mediterranean Conference on Control and Automation.
Publikováno v:
2006 14th Mediterranean Conference on Control and Automation.
The present paper approaches the inventory control problem in supply chains. A classical solution of this problem is based on base-stock policy which, more recently, has been improved using large deviations (LD) techniques and introducing the concept
Publikováno v:
International Journal of Services Sciences. 2:1
This paper addresses the theme of investment under uncertainty in services. We specifically apply principles of contingent-claims analysis to underline the value of flexibility, i.e., the real options, embedded in service level agreements (SLAs) and
Publikováno v:
Scopus-Elsevier
We develop a distributed multi-agent form of actor-critic algorithms for solving Markov decision problems. The proposed algorithm allows multiple agents to simultaneously explore the state-control space and communicate to exchange a limited amount of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::07b7822ed5964f240aaf61cbf520a711
http://www.scopus.com/inward/record.url?eid=2-s2.0-80051585277&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-80051585277&partnerID=MN8TOARS
Autor:
Paris Pennesi, Giuseppe Conte
Publikováno v:
Scopus-Elsevier
This paper describes a model predictive control strategy to tackle the inventory control problem in Supply Chains. The problem is formulated as a receding-horizon optimization problem and the market demand is considered an external unknown disturbanc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::717dc9c9a4652c6e85a95c51ebf3e91c
http://www.scopus.com/inward/record.url?eid=2-s2.0-79960705327&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-79960705327&partnerID=MN8TOARS