IQSon: A Context-aware Negotiator Agent with Enhanced Utility and Decision Making Speed

Mirzayi, Sahar; Taghiyareh, Fattaneh; Kazemi, Seyed Mohammad Hussein

doi:10.1109/istel.2018.8661115

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…We base our agent's architecture on BOA (bidding strategy, opponent model, and acceptance condition) architecture, introduced by Baarslag et al (2014) [6], which has become a common framework for developing negotiating agents [49,10,35,23]. The BOA architecture defines the different components in an agent's strategy used for its decision-making process, which are: opponent model, bidding strategy and acceptance condition.…”

Section: Strategy Designmentioning

confidence: 99%

A Negotiating Strategy for a Hybrid Goal Function in Multilateral Negotiation

Stern¹,

Kraus²,

Sarne³

2022

Preprint

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In various multi-agent negotiation settings, a negotiator's utility depends, either partially or fully, on the sum of negotiators' utilities (i.e., social welfare). While the need for effective negotiating-agent designs that take into account social welfare has been acknowledged in recent work, and even established as a category in automated negotiating agent competitions, very few designs have been proposed to date. In this paper, we present the design principles and results of an extensive evaluation of agent HerbT+, a negotiating agent aiming to maximize a linear tradeoff between individual and social welfare. Our evaluation framework relies on the automated negotiating agents competition (ANAC) and includes a thorough comparison of performance with the top 15 agents submitted between 2015-2018 based on negotiations involving 63 agents submitted to these competitions. We find that, except for a few minor exceptions, when social-welfare plays a substantial role in the agent's goal function, our agent outperforms all other tested designs.

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Section: Strategy Designmentioning

confidence: 99%

A Negotiating Strategy for a Hybrid Goal Function in Multilateral Negotiation

Stern¹,

Kraus²,

Sarne³

2022

Preprint

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“…Using probabilistic reasoning to implement negotiation agents provides a clear and inbuilt way of providing that predictability, and also provides a way to incorporate a broader view of the situation into the workings of an agent instead of only the issues pertaining to the actual negotiation. It has already been seen in [27] that context awareness has advantages for negotiation agents. Applications using probabilistic reasoning methods such as ProbLog [32] could incorporate information from various sensors, such as demonstrated by [39], to be incorporated in both bidding strategies and opponent modelling.…”

Section: An Rau Implementation For Better Predictability Of Outcome A...mentioning

confidence: 99%

The current state of automated negotiation theory: a literature review

Vente,

Kimmig,

Preece

et al. 2020

Preprint

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Automated negotiation can be an efficient method for resolving conflict and redistributing resources in a coalition setting. Automated negotiation has already seen increased usage in fields such as e-commerce and power distribution in smart girds, and recent advancements in opponent modelling have proven to deliver better outcomes. However, significant barriers to more widespread adoption remain, such as lack of predictable outcome over time and user trust. Additionally, there have been many recent advancements in the field of reasoning about uncertainty, which could help alleviate both those problems. As there is no recent survey on these two fields, and specifically not on their possible intersection we aim to provide such a survey here.

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