Skip to main navigation
Skip to search
Skip to main content
Korea University Pure Home
Search content at Korea University Pure
Home
Profiles
Research units
Equipment
Research output
Press/Media
Optimal Mechanism in a Dynamic Stochastic Knapsack Environment
Jihyeok Jung
, Chan Oi Song
, Deok Joo Lee
*
,
Kiho Yoon
*
Corresponding author for this work
Department of Economics
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
1
Link opens in a new tab
Citation (Scopus)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Optimal Mechanism in a Dynamic Stochastic Knapsack Environment'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Buyers
100%
Incentive Mechanism
100%
Optimal Mechanism
100%
Dynamic Stochastic
100%
Stochastic Knapsack
100%
Two Dimensional
50%
Monte Carlo Simulation
50%
Simulation-based
50%
Private Information
50%
Discrete-time
50%
Reinforcement Learning
50%
Policy-based
50%
Piecewise Linear
50%
Regression Method
50%
Model Features
50%
Individual Rationality
50%
Marginal Value
50%
Allocation Policy
50%
Optimal Policy
50%
Seller
50%
Dynamic Mechanism
50%
Bellman Equation
50%
Feasibility Conditions
50%
Payment Policy
50%
Rationality Conditions
50%
Linear Utility Function
50%
Penalty Scheme
50%
Mathematics
Stochastics
100%
Incentive compatibility
100%
Monte Carlo
50%
Approximates
50%
Discrete Time
50%
Marginals
50%
Bellman Equation
50%
Optimal Policy
50%
Utility Function
50%
Feasibility Condition
50%
Computer Science
Knapsack
100%
Monte Carlo Simulation
50%
Utility Function
50%
Reinforcement Learning
50%
Regression Method
50%
discrete-time
50%
Economics, Econometrics and Finance
Incentives
100%
Utility Function
50%
Monte Carlo Simulation
50%
Private Information
50%