In this paper, we extend the notion of person by person optimization to binary decision spaces. The novelty of our approach is the adaptation to a dynamic team context of notions borrowed from the pseudo-boolean optimization field as completely local-global or unimodal functions and submodularity. We also generalize the concept of pbp optimization to the case where the Decision Makers (DMs) make decisions sequentially in groups of m, we call it mbm optimization. The main contribution are certain sufficient conditions, verifiable in polynomial time, under which a pbp or an mbm optimization algorithm leads to the team-optimum. We also show that there exists a subclass of sub-modular team problems, recognizable in polynomial time, for which the convergence is guaranteed if the pbp algorithm is opportunely initialized.

Generalized person-by-person optimization in team problems with binary decisions

PESENTI, Raffaele
2008-01-01

Abstract

In this paper, we extend the notion of person by person optimization to binary decision spaces. The novelty of our approach is the adaptation to a dynamic team context of notions borrowed from the pseudo-boolean optimization field as completely local-global or unimodal functions and submodularity. We also generalize the concept of pbp optimization to the case where the Decision Makers (DMs) make decisions sequentially in groups of m, we call it mbm optimization. The main contribution are certain sufficient conditions, verifiable in polynomial time, under which a pbp or an mbm optimization algorithm leads to the team-optimum. We also show that there exists a subclass of sub-modular team problems, recognizable in polynomial time, for which the convergence is guaranteed if the pbp algorithm is opportunely initialized.
2008
Proceedings of the American Control Conference 2008
File in questo prodotto:
File Dimensione Formato  
04586577.pdf

non disponibili

Tipologia: Documento in Post-print
Licenza: Accesso chiuso-personale
Dimensione 174.18 kB
Formato Adobe PDF
174.18 kB Adobe PDF   Visualizza/Apri

I documenti in ARCA sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/26084
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 8
  • ???jsp.display-item.citation.isi??? 8
social impact