Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Pramod Vaidyanathan

dblp:52/8860 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none

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

Theory of computation · 1

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
1 paper
Algorithmic game theory and mechanism design · 91% Mathematical optimization · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design
equilibrium computation
0.112010
Information concealing games · IEEE Trans. Inf. Theory 2010
Algorithmic game theory and mechanism design › solution concepts in games › equilibrium concepts
perfect bayesian equilibrium
0.112010
Information concealing games · IEEE Trans. Inf. Theory 2010
Algorithmic game theory and mechanism design › imperfect information games
signaling game
0.112010
Information concealing games · IEEE Trans. Inf. Theory 2010
Mathematical optimization
linear programming
0.012010
Information concealing games · IEEE Trans. Inf. Theory 2010

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

linear programming · 0.1approximation algorithm · 0.1
YearPublicationVenuePosition
2010 Information concealing games
abstract
A system with ann-dimensional state vector and acontrollerand anactoris considered. The controller has complete information about the system state, and reveals a certain “minimum” amount of information to the actor. The actor takes certain actions based on the information the controller reveals, and the actions fetch certain utilities for each entity. Both the controller and actor seek to maximize their individual utilities by respectively selecting the information to reveal and the actions to adopt. This decision problem forms the basis of several technical and social systems, and can be formulated as a signaling game. It is shown that the Perfect Bayesian Equilibrium of this game has several counterintuitive properties and can be obtained as a saddle point of a different two person zero sum game. The computation time for saddle points using standard linear programs however turns out to be superexponential inn, which leads to computational intractability even for moderaten. Algorithms for computing saddle point policies using a computation time that is exponential innare presented. Finally, simple linear time computable policies that approximate the saddle-point policies within guaranteeable approximation ratios are obtained.
Saswati Sarkar, Eitan Altman, Pramod Vaidyanathan
IEEE Trans. Inf. Theory3