Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets: Amec 2013, Saint Paul, Mn, Usa, May 6, 2013, T

ISBN-13: 9783319132174 / Angielski / Miękka / 2014 / 171 str.

Sofia Ceppi; Esther David; Vedran Podobnik

Opis

This volume contains 12 thoroughly refereed and revised papers detailing recent advances in research on designing trading agents and mechanisms for agent-mediated e-commerce. They were originally presented at three events: the Workshop on Agent-Mediated Electronic Commerce (AMEC 2013), co-located with AAMAS 2013 in Saint Paul, MN, USA, in May 2013; the Workshop on Trading Agent Design and Analysis (TADA 2013), co-located with AAAI 2013 in Bellevue, WA, USA, in July 2013; and the Joint Workshop on Trading Agent Design and Analysis (TADA 2014) and Agent-Mediated Electronic Commerce (AMEC 2014), co-located with AAMAS 2014 in Paris, France, in May 2014. Given the breadth of research topics in this field, the range of topics addressed in these papers is correspondingly broad. These include the study of theoretical issues related to the design of interaction protocols and marketplaces; the design and analysis of automated trading strategies used by individual agents; and the deployment of such strategies, in times as part of an entry to the trading agent competition.

Spis treści

An Analysis of Power Trading Agent Competition 2014.- Towards Modeling Securities Markets as a Society of Heterogeneous Trading Agents.- A Market-Based Coordinated Negotiation for QoS-Aware Service Selection.- Optimal Agendas for Sequential Negotiations.- An Empirical Analysis of QuiBids’ Penny Auctions.- Analysis of Fairness and Incentives of Profit Sharing Schemes in Group Buying.- Distributed Prediction Markets Modeled by Weighted Bayesian Graphical Games.- A Successful Broker Agent for Power TAC.- Online Double Auction for Perishable Goods.- Designing Tariffs in a Competitive Energy Market Using Particle Swarm Optimization Techniques.- Classification Driven Detection of Opportunistic Bids in TAC SCM.- An Intelligent Learning Mechanism for Trading Strategies for Local Energy Distribution.