Wu, Haoyang (2010): Quantum mechanism helps agents combat Pareto-inefficient social choice rules.
Wu, Haoyang (2010): A classical algorithm to break through Maskin's theorem for small-scale cases.
Wu, Haoyang (2010): Two examples to break through classical theorems on Nash implementation with two agents.
Wu, Haoyang (2010): Bugs in the proofs of revelation principle.
Wu, Haoyang (2011): Two-agent Nash implementation: A new result.
Wu, Haoyang (2011): Quantum and algorithmic Bayesian mechanisms.
Wu, Haoyang (2011): Subgame perfect implementation: A new result.
Wu, Haoyang (2010): Bugs in the proofs of revelation principle.
Wu, Haoyang (2010): A note on revelation principle from an energy perspective.
Wu, Haoyang (2011): A note on revelation principle from an energy perspective.
Wu, Haoyang (2011): A novel result on the revenue equivalence theorem.
Wu, Haoyang (2011): On amending the sufficient conditions for Nash implementation.
Wu, Haoyang (2011): On amending the Maskin's theorem by using complex numbers.
Wu, Haoyang (2011): A non-cooperative Pareto-efficient solution to a one-shot Prisoner's Dilemma.
Wu, Haoyang (2011): Quantum Bayesian implementation.
Wu, Haoyang (2011): On amending the Maskin's theorem by using complex numbers.
Wu, Haoyang (2012): Traditional sufficient conditions for Nash implementation may fail on Internet.
Wu, Haoyang (2016): A Bayesian implementable social choice function cannot be implemented by a direct mechanism.
Wu, Haoyang (2016): A costly Bayesian implementable social choice function may not be truthfully implementable.
Wu, Haoyang (2018): The revelation principle does not always hold when strategies of agents are costly.
Wu, Haoyang (2019): A note on the definition of Bayesian Nash equilibrium of a mechanism when strategies of agents are costly actions.
Wu, Haoyang (2019): Profitable Bayesian implementation in one-shot mechanism settings.
Wu, Haoyang (2020): The revelation principle fails when the format of each agent's strategy is an action.
Wu, Haoyang (2022): A type-adjustable mechanism where the designer may obtain more payoffs by optimally controlling distributions of agents' types.
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