We define a new protocol rule, Now or Never (NoN), for bilateral negotiation processes which allows self-motivated competitive agents to efficiently carry out multi-variable negotiations with remote untrusted parties, where privacy is a major concern and agents know nothing about their opponent. By building on the geometric concepts of convexity and convex hull, NoN ensures a continuous progress of the negotiation, thus neutralising malicious or inefficient opponents. In par- ticular, NoN allows an agent to derive in a finite number of steps, and independently of the behaviour of the opponent, that there is no hope to find an agreement. To be able to make such an inference, the interested agent may rely on herself only, still keeping the highest freedom in the choice of her strategy. We also propose an actual NoN-compliant strategy for an automated agent and evaluate the computational feasibility of the overall approach on instances of practical size.

Now or never: negotiating efficiently with unknown counterparts / Mancini, Toni. - ELETTRONICO. - 1451:(2015), pp. 47-61. (Intervento presentato al convegno 22nd RCRA International Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion 2015, RCRA 2015 - A Workshop of the 14th International Conference of the Italian Association for Artificial Intelligence, AI*IA 2015 tenutosi a ferrara nel 2015).

Now or never: negotiating efficiently with unknown counterparts

MANCINI, Toni
2015

Abstract

We define a new protocol rule, Now or Never (NoN), for bilateral negotiation processes which allows self-motivated competitive agents to efficiently carry out multi-variable negotiations with remote untrusted parties, where privacy is a major concern and agents know nothing about their opponent. By building on the geometric concepts of convexity and convex hull, NoN ensures a continuous progress of the negotiation, thus neutralising malicious or inefficient opponents. In par- ticular, NoN allows an agent to derive in a finite number of steps, and independently of the behaviour of the opponent, that there is no hope to find an agreement. To be able to make such an inference, the interested agent may rely on herself only, still keeping the highest freedom in the choice of her strategy. We also propose an actual NoN-compliant strategy for an automated agent and evaluate the computational feasibility of the overall approach on instances of practical size.
2015
22nd RCRA International Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion 2015, RCRA 2015 - A Workshop of the 14th International Conference of the Italian Association for Artificial Intelligence, AI*IA 2015
Agents; Multi agent systems; bilateral negotiation
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Now or never: negotiating efficiently with unknown counterparts / Mancini, Toni. - ELETTRONICO. - 1451:(2015), pp. 47-61. (Intervento presentato al convegno 22nd RCRA International Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion 2015, RCRA 2015 - A Workshop of the 14th International Conference of the Italian Association for Artificial Intelligence, AI*IA 2015 tenutosi a ferrara nel 2015).
File allegati a questo prodotto
File Dimensione Formato  
Mancini_now_2015.pdf

accesso aperto

Note: Articolo
Tipologia: Versione editoriale (versione pubblicata con il layout dell'editore)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 795.82 kB
Formato Adobe PDF
795.82 kB Adobe PDF

I documenti in IRIS 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/11573/948046
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact