This work was presented at HAIDM 2014. The 2014 workshop on Human-Agent Interaction Design and Models was co-organised by SmartSociety.

Abstract: This paper deals with platforms that provide agents easier access to the type of opportunities in which they are interested (e.g., eCommerce platforms, used cars bulletins and dating web-sites). We show that under various common service schemes, a platform can benefit from not necessarily listing all the opportunities with which it is familiar, even if there is no marginal cost for listing any additional opportunity. The main implication of this result is that platforms should extract their expected-profit-maximizing service terms not based solely on the fees charged from users, but they should also use the subset that will be listed as the decision variable in the optimization problem. The analysis applies to four well-known service schemes that a platform may use to price its services. We show that neither of these schemes generally dominates the others or is dominated by any of the others. For the common case of homogeneous preferences, however, several dominance relationships can be proved, enabling the platform to identify the schemes that should be used as a default. Furthermore, the analysis provides a game-theoretic search-based explanation for a possible preference of buyers to pay for the service rather than receive it for free (e.g., when the service is sponsored by ads), a phenomena that has been justified in prior literature typically with the argument of willingness to pay a premium for an ad-free experience or more reliable platforms. The paper shows that this preference can hold both for the users and the platform in a given setting, even if both sides are fully strategic.

Keywords: Platforms and Services, Economics of Information, Two-Sided Markets, Price of Free, Service Schemes.

Citation: Chen Hajaj and David Sarne. Strategic Information Platforms – Selective Disclosure and The Price of “Free”.

Download: http://bit.ly/1VwVZSz

EASSS 2014 will be held at the Technical University of Crete, Chania, Greece , from the 14th July to the 18th July 2014. Primarily focussed on single and multi-agent systems, this year’s school will feature additional courses covering topics related to social intelligence. It will be co-organised by the European Network for Social Intelligence and serves as their official Summer School.

Please note the deadline for early registration, which is the 31st May 2014. You can view the school’s complete schedule here.

Smart Society’s M. Rovatsos has won second prize for best challenge and vision paper in AAMAS 2014!

Abstract: This paper proposes social computation, i.e. large-scale man-machine collaboration mediated by digital interaction media, as a vision for future intelligent systems, and as a new challenge for multiagent systems research. We claim that the study of social computation suggests a re-interpretation of many traditional AI endeavours, has huge potential application benefits, and presents the field of multiagent systems with novel, exciting research questions. We introduce an abstract model of social computation that helps capture some of its core research problems more precisely. We explore the potential contribution of multiagent systems technologies to the solution of these problems by exposing the close relationship between social computation and existing methods in multiagent systems. We describe how these methods could be reused in this novel application context, what methodological implications this has, and argue that the resulting cross-fertilisation will be highly beneficial for both sides.

Keywords: social computation, human-based computation, crowdsourcing, collective intelligence.

doi: http://dl.acm.org/citation.cfm?id=2617388.2617432

Citation: M. Rovatsos. Multiagent Systems for Social Computation (challenge paper), Thirteenth International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2014), May 5-9, 2014.

Download: http://bit.ly/1W9uFYU