Abridgement of HANA: a Human-Aware Negotiation Architecture
Publication Type:
Conference PaperSource:
European Workshop on Multi-agent Systems (EUMAS 2012) (2012)Abstract:
HANA is an agent architecture suitable for multiple bilateral negotiations in realistic problems involving humans. The architecture deals with prenegotiation and provides a new search and negotiation technique where search and negotiation go hand in hand: the former providing offers to propose, and the later providing commitments for pruning the search space, and information for fine-tuning the evaluation of offers. The architecture represents graded beliefs, dynamic desires and general intentions. It can be extended incorporating new behavioural models that can enrich the negotiation strategy with new information.
Automated Negotiation for Package Delivery
Publication Type:
Conference PaperSource:
Workshop on Technologies for the Organisation, Adaptation and Simulation of Transportation Systems (TOASTS@SASO), Lyon, France (2012)Keywords:
Negotiation; Search; NB3; LogisticsAbstract:
Package delivery companies compete with each other and have costumers spread over wide areas. We propose a negotiation algorithm that allows companies and individual postmen to negotiate over who delivers what package. This way, package delivery can be made more efficient, yielding a higher profit and/or lower costs for all parties. Our system does not force competing companies to co-operate, but proposes solutions that allow all parties to increase their individual profit.
Overview of HANA: a Human-Aware Negotiation Architecture
Branch and Bound for Negotiations in Large Agreement Spaces
Publication Type:
Conference PaperSource:
The 11th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2012), Valencia, Spain (2012)Keywords:
Negotiation; Search; Branch and Bound; Negotiating Salesmen ProblemAbstract:
We introduce a new multiagent negotiation algorithm for large and complex domains, called NB3. It applies Branch & Bound to search for good off ers to propose. To analyze its performance we present a new problem called the Negotiating Salesmen Problem. We have conducted some experiments with NB3 from which we conclude that it manages to decrease the traveling cost of the agents significantly, that it outperforms random search and that it scales well with the complexity of the problem.
Negotiation Based Branch and Bound and the Negotiating Salesmen Problem
Publication Type:
Conference PaperSource:
Proceedings of the 14th International Conference of the Catalan Association for Artificial Intelligence (CCIA 2011), IOS Press, Lleida, Catalonia, Spain, p.p.91-100 (2011)Abstract:
We introduce a new multiagent negotiation algorithm that explores the space of joint plans of action: NB3. Each negotiator generates a search tree by considering both actions performed by itself and actions performed by others. In order to test the algorithm we present a new variant of the Traveling Salesman Problem, in which there is not one, but many salesmen. The salesmen need to negotiate with each other in order to minimize the distances they have to cover. Finally we present the results of some tests we did with a simple implementation of the algorithm for this problem.
NB3: Negotiation-Based Branch&Bound
Publication Type:
ReportSource:
IIIA-CSIC, Bellaterra, Barcelona, p.1-13 (2011)Accession Number:
TR–IIIA–2011–03Abstract:
In this paper I introduce a new multiagent negotiation algorithm that explores the space of joint plans of action: $NB^3$. Each negotiator generates a search tree by considering both actions performed by itself and actions performed by others. The algorithm prunes the nodes of the tree that require rejected actions of others, and focusses on the most promising nodes by using appropriate heuristics.
