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Anton Likhodedov

dblp:17/4931 · DBLP profile ↗
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4ranked-venue papers
4as first author
0since 2021 · last 2005
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 4 · 4 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2 · 2 first-authorTheory of computation · 2 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
4 papers
Algorithmic game theory and mechanism design · 87% Approximation and online algorithms · 13%
Artificial intelligence
1 paper
Multi-agent systems · 100%

Topics — the 8 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design › auction theory
combinatorial auction
0.122005
Approximating Revenue-Maximizing Combinatorial Auctions · AAAI 2005
Methods for Boosting Revenue in Combinatorial Auctions · AAAI 2004
Algorithmic game theory and mechanism design
revenue maximization
0.122005
Approximating Revenue-Maximizing Combinatorial Auctions · AAAI 2005
Methods for Boosting Revenue in Combinatorial Auctions · AAAI 2004
Algorithmic game theory and mechanism design › mechanism design
auction design
0.122004
Mechanism for optimally trading off revenue and efficiency in multi-unit auctions · EC 2004
Auction mechanism for optimally trading off revenue and efficiency · EC 2003
Algorithmic game theory and mechanism design › mechanism design › auction design
revenue-efficiency tradeoff
0.122004
Mechanism for optimally trading off revenue and efficiency in multi-unit auctions · EC 2004
Auction mechanism for optimally trading off revenue and efficiency · EC 2003
Approximation and online algorithms
approximation
0.112005
Approximating Revenue-Maximizing Combinatorial Auctions · AAAI 2005
Algorithmic game theory and mechanism design › mechanism design › auction design
multi-unit auction
0.012004
Mechanism for optimally trading off revenue and efficiency in multi-unit auctions · EC 2004
Algorithmic game theory and mechanism design › mechanism design › auction design
reserve price
0.012003
Auction mechanism for optimally trading off revenue and efficiency · EC 2003
Knowledge, reasoning and agents › Multi-agent systems › automated negotiation
auction mechanisms
0.012004
Methods for Boosting Revenue in Combinatorial Auctions · AAAI 2004

Methods — techniques the papers use, named apart from their topics

mechanism design · 0.1vickrey auction · 0.1myerson auction · 0.1approximation algorithm · 0.1dominant strategy mechanism · 0.0constrained optimization · 0.0
YearPublicationVenuePosition
2005 Approximating Revenue-Maximizing Combinatorial Auctions
Anton Likhodedov, Tuomas Sandholm
AAAI1
2004 Methods for Boosting Revenue in Combinatorial Auctions
Anton Likhodedov, Tuomas Sandholm
AAAI1
2004 Mechanism for optimally trading off revenue and efficiency in multi-unit auctions
abstract
We study auctioning multiple units of the same good to potential buyers with single unit demand (i.e. every bidder wants only one unit of the good). Depending on the objective of the seller, different selling mechanisms are desirable. The Vickrey auction with a truthful reserve price is optimal when the objective is efficiency - allocating the units to the parties who values them the most. The Myerson auction is optimal when the objective is the seller's expected utility. These two objectives are generally in conflict, and cannot be maximized with one mechanism. In many real-world settings---such as privatization and competing electronic marketplaces---it is not clear that the objective should be either efficiency or seller's expected utility. Typically, one of these objectives should weigh more than the other, but both are important. We account for both objectives by designing a new deterministic dominant strategy auction mechanism that maximizes expected social welfare subject to aminimum constraint on the seller's expected utility. This way the seller can maximize social welfare subject to doing well enough for himself.
Anton Likhodedov, Tuomas Sandholm
EC1
2003 Auction mechanism for optimally trading off revenue and efficiency
abstract
We study selling one indivisible object to multiple potential buyers. Depending on the objective of the seller, different selling mechanisms are desirable. The Vickrey auction with a truthful reserve price is optimal when the objective is efficiency (i.e., allocating the object to the party who values it the most). The Myerson auction is optimal when the objective is the seller's expected utility. These two objectives are generally in conflict, and cannot be maximized with one mechanism. In many real-world settings---such as privatization and competing electronic marketplaces---it is not clear that the objective should be either efficiency or seller's expected utility. Typically, one of these objectives should weigh more than the other, but both are important. We account for importance of both objectives by designing a new deterministic auction mechanism that maximizes expected social welfare subject to a minimum constraint on the seller's expected utility. This way the seller can expect to do well enough for himself, while maintaining the attractive properties of the mechanism.
Anton Likhodedov, Tuomas Sandholm
EC1