A MAS Approach for Group Recommendation Based on Negotiation Techniques

Villavicencio, Christian; Schiaffino, Silvia; Díaz-Pace, J. Andrés; Monteserin, Ariel; Demazeau, Yves; Adam, Carole

doi:10.1007/978-3-319-39324-7_19

Cited by 11 publications

(15 citation statements)

References 11 publications

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“…The entities make use of their experience and help each other avoid complex negotiation processes which, considering similar past experiences, are less likely to end in a successful allocation of resources. Villavicencio et al used AT to create a movie recommendation system for groups of people [ 25 ]. The use of AT in this work made it possible to satisfy user preferences more equitably than traditional agreement methodologies.…”

Section: Related Workmentioning

confidence: 99%

Agreement Technologies for Energy Optimization at Home

González‐Briones

Chamoso

Prieta

et al. 2018

Sensors

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Nowadays, it is becoming increasingly common to deploy sensors in public buildings or homes with the aim of obtaining data from the environment and taking decisions that help to save energy. Many of the current state-of-the-art systems make decisions considering solely the environmental factors that cause the consumption of energy. These systems are successful at optimizing energy consumption; however, they do not adapt to the preferences of users and their comfort. Any system that is to be used by end-users should consider factors that affect their wellbeing. Thus, this article proposes an energy-saving system, which apart from considering the environmental conditions also adapts to the preferences of inhabitants. The architecture is based on a Multi-Agent System (MAS), its agents use Agreement Technologies (AT) to perform a negotiation process between the comfort preferences of the users and the degree of optimization that the system can achieve according to these preferences. A case study was conducted in an office building, showing that the proposed system achieved average energy savings of 17.15%.

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Section: Related Workmentioning

confidence: 99%

Agreement Technologies for Energy Optimization at Home

González‐Briones

Chamoso

Prieta

et al. 2018

Sensors

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“…One way for selecting the conceding agent(s) is to apply the Zeuthen strategy [39] around the concept of willingness to risk conict (WRC). This strategy was initially designed to be used in bilateral negotiations and later extended to work in multi-lateral ones, as explained in [12] 3 . The WRC for ag i (W RC i ) is then given by Equation 2:…”

Section: Concession Decision Rulementioning

confidence: 99%

“…The single-user recommender (SUR) system used by the agents in MA-GReS , TRADGRec-PA and TRADGRec-RA, was implemented using the Duine 9 http://grouplens.org/datasets/movielens/ 10 https://www.yelp.com/dataset_challenge framework 11 and the Mahout framework 12 . Duine was used in the rst implementation stages and helped us to gain condence that the approach was viable [44,12]. Nonetheless, Duine had some limitations regarding the loading time of the data models, which made it unsuitable for a responsive recommendation application 13 .…”

Section: Description Of Baselinesmentioning

confidence: 99%

“…Particularly, the negotiation method is expected to generate recommendations that satisfy the group members more uniformly than traditional approaches. Along this line, we proposed a multi-agent approach for group recommendation called PUMAS-GR [12], which was later re-named to MAGReS (Multi-Agent Group Recommender System ). In MAGReS, a personal agent represents each user of a group.…”

Section: Introductionmentioning

confidence: 99%

“…The general idea of the approach was initially presented in [12], including preliminary evaluation results. However, the agents were all equipped with one single acceptance criterion for item proposals, which did not allow agent personalization by the users.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Group recommender systems: A multi-agent solution

Villavicencio

Schiaffino

Díaz-Pace

et al. 2019

Knowledge-Based Systems

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Providing recommendations to groups of users has become a promising research area, since many items tend to be consumed by groups of people. Various techniques have been developed aiming at making recommendations to a group as a whole. Most works use aggregation techniques to combine preferences, recommendations or proles. However, satisfying all group members in an even way still remains as a challenge. To deal with this problem, we propose an extension of a multi-agent approach based on negotiation techniques for group recommendation. In the approach, we use the multilateral Monotonic Concession Protocol (MCP) to combine individual recommendations into a group recommendation.In this work, we extend the MCP protocol to allow users to personalize the behavior of the agents. This extension was evaluated in two dierent domains (movies and points of interest) with satisfactory results. We compared our approach against dierent baselines, namely: a preference aggregation algorithm, a recommendation aggregation algorithm, and a simple one-step negotiation.The results show evidence that, when using our negotiation approach, users in the groups are more uniformly satised than with traditional aggregation approaches.

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Co-exploring a Search Space in a Group Recommender System

Yodogawa

Kuwabara

2019

Intelligent Information and Database Systems

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A MAS Approach for Group Recommendation Based on Negotiation Techniques

Cited by 11 publications

References 11 publications

Agreement Technologies for Energy Optimization at Home

Agreement Technologies for Energy Optimization at Home

Group recommender systems: A multi-agent solution

Co-exploring a Search Space in a Group Recommender System

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