International Conference on Information and Knowledge Technology

فارسی

Home / دوازدهمین کنفرانس بین المللی فناوری اطلاعات و دانش

Experimental analysis of automated negotiation agents in modeling Gaussian bidders

Authors :

Fatemeh Hassanvand¹ Faria Nassiri-Mofakham²

1- دانشگاه اصفهان 2- دانشگاه اصفهان

Keywords :

automated negotiating agents, Gaussian utility function, Gaussian bidders, preference estimation

Abstract :

Automated negotiating agents are usually designed and implemented in a general way so that they can negotiate successfully in front of a vast variety of opponents. In real world, most opponents are single-peaked. Gaussian agents that use such distribution function to rate the negotiation items are important sort of such opponents. Modeling the opponents is of great importance, since it enables us to adjust our next decisions accordingly. This can bring us short –time compromises, ideal eventual utility, more satisfaction, and so on. In negotiating with Gaussian opponents, the estimation of the opponent's peak point is the core. In this regard, we have paid a particular attention on how accurate the existing automated agents attended in Automated Negotiating Agents Competition (ANAC) during 2010-2019 can model Gaussian bidders and showed the experiments result.

List of archived papers

طراحی و پیاده سازی بستر اجرای بازی جنگ سایبری

مریم نصراصفهانی - بهروز ترک لادانی - بهروز شاهقلی قهفرخی - حسین قجاوند بلتیجه - نوید شیرمحمدی - مهدی شمس - محمدامین آقاکبیری

Improving Personalized Federated Learning-based QoE Assessment using Clustering

Skokufe Motaharipour - Behrouz Shahgholi Ghahfarokhi - Saeid Afshari

Stock Market Prediction Using Hard and Soft Data Fusion

Saeed Mohammadi Dashtaki - Masoud Alizadeh - Behzad Moshiri

تاثیر مدیریت دانش مشتری بر توسعه محصول جدید و نوآورانه با رویکرد مدل سازی معادلات ساختاری با استفاده از حداقل مربعات جزئی: مطالعۀ موردی شرکت کاله

دکتر آرش خسروی - سیده فاطمه حسینی - دکتر مرتضی رجب زاده آرش خسروی - سیده فاطمه حسینی - مرتضی رجب زاده -

ISPREC: Integrated Scientific Paper Recommendation using heterogeneous information network

Elaheh Jafari - Dr Bita Shams - Dr Saman Haratizadeh

A Novel Approach to Data mining algorithms and IoT based data mining machine learning

Danial Ramezani - Seyed Hossein Siadat

Extending Interaction Flow Modeling Language as a Profile for Form-making Systems

Ghazaleh Shahin - Dr Bahman Zamani

A Graph Attention-Based Autoencoder for Critical Path Anomaly Detection in Microservices

Mahdi Naderi - Hossein Momeni - Shayan Shahini

A Novel Decentralized Privacy Preserving Federated Learning Model for Healthcare Applications

Saba Ameri - Reza Ebrahimi Atani

Targeted Vaccination for COVID-19 Using Mobile Communication Networks

Mohammadmohsen Jadidi - Pegah Moslemi - Saeed Jamshidiha - Iman Masroori - Abbas Mohammadi - Vahid Pourahmadi

Samin Hamayesh - Version 40.3.1