Invited Session Wed.2.H 0111

Wednesday, 13:15 - 14:45 h, Room: H 0111

Cluster 13: Logistics, traffic, and transportation [...]

New algorithms for new pricing models

 

Chair: Hamid Nazerzadeh

 

 

Wednesday, 13:15 - 13:40 h, Room: H 0111, Talk 1

Luis Manuel Briceño-Arias
Optimal continuous pricing with strategic consumers

Coauthor: José R. Correa

 

Abstract:
An interesting problem in mechanism design is that of finding
mechanisms to sell a single item when the number of bidders is random. In this paper we take a step further to the static situation and derive an optimal pricing scheme when selling a single item to strategic consumers that arrive over time according to a random process. Combining auction theory and recent work on pricing with strategic consumers, we derive the optimal pricing mechanism in this situation under reasonable conditions.

 

 

Wednesday, 13:45 - 14:10 h, Room: H 0111, Talk 2

Ashish Goel
Reputation and trust in social networks

Coauthors: Bahman Bahmani, Goel Dandekar, Ramesh Govindan, Ian Post, Michael Wellman, Bryce Wiedenbeck

 

Abstract:
Automated reputation and trust systems play an ever increasing role in the emerging networked society. We will first describe a model of networked trust that functions by exchange of IOUs among nodes. Informally, every node acts as a bank and prints its own currency, which is then used to purchase services within the network. Such "trust networks'' are robust to infiltration, since any node only accepts currency printed by other nodes that it directly trusts. We will analyze the liquidity of this model, i.e., the number of transactions that such a network can support. We will show that in many interesting cases, the liquidity of these trust networks is comparable to a system where currency is issued by a single centralized bank. We will then show that in simple networks, rational agents allocate trust in a socially optimal manner.

 

 

Wednesday, 14:15 - 14:40 h, Room: H 0111, Talk 3

Azarakhsh Malekian
Bayesian optimal auctions via multi- to single-agent reduction

Coauthors: saeed alaei, hu fu, nima haghpanah, jason hartline

 

Abstract:
We study an abstract optimal auction problem for a single good or service. This problem includes environments where agents have budgets, risk preferences, or multi-dimensional preferences over several possible configurations of the good (furthermore, it allows an agent's budget and risk preference to be known only privately to the agent). These are the main challenge areas for auction theory. A single-agent problem is to optimize a given objective subject to a constraint on the maximum probability with which each type is allocated, a.k.a., an allocation rule. Our approach is a reduction from multi-agent mechanism design problem to collection of single-agent problems. We focus on maximizing revenue, but our results can be applied to other objectives (e.g., welfare).
An optimal multi-agent mechanism can be computed by a linear/convex program on interim allocation rules by simultaneously optimizing several single-agent mechanisms subject to joint feasibility of the allocation rules.

 

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