We consider settings where a collective intelligence is formed by aggregating information contributed from many independent agents, such as product reviews, community sensing, or opinion polls. We propose a novel mechanism that elicits both private signals and beliefs. The mechanism extends the previous versions of the Bayesian Truth Serum (the original BTS, the RBTS, and the multi-valued BTS), by allowing small populations and non-binary private signals, while not requiring additional assumptions on the belief updating process. For priors that are sufficiently smooth, such as Gaussians, the mechanism allows signals to be continuous
The problem of peer prediction is to elicit information from agents in settings without any objectiv...
Integrating information gained by observing others via So-cial Bayesian Learning can be beneficial f...
Abstract. If a group as a whole is modelled as a single Bayesian agent, what should its beliefs be? ...
Several mechanisms have been proposed for incentivizing truthful reports of a private signals owned ...
Peer prediction mechanisms allow the truthful elicitation of private signals (e.g., experiences, or ...
The modern web critically depends on aggregation of information from self-interested agents, for exa...
We study learning statistical properties from strategic agents with private information. In this pro...
textabstractFinancial markets reveal what investors think about the future, and prediction markets a...
In this dissertation, we analyze the interaction between intelligent and selfish agents in non-coope...
Abstract Peer-prediction mechanisms elicit information about unverifiable or subjective states of th...
In this paper, we propose a new mechanism - the Disagreement Mechanism - which elicits privately-hel...
Inferring the information structure of other agents is necessary to derive optimal mechanisms/signal...
We study a setting where Bayesian agents with a common prior have private information related to an ...
We outline how to create a mechanism that provides an optimal way to elicit, from an arbitrary group...
We consider a participatory sensing scenario where a group of private sensors observes the same phen...
The problem of peer prediction is to elicit information from agents in settings without any objectiv...
Integrating information gained by observing others via So-cial Bayesian Learning can be beneficial f...
Abstract. If a group as a whole is modelled as a single Bayesian agent, what should its beliefs be? ...
Several mechanisms have been proposed for incentivizing truthful reports of a private signals owned ...
Peer prediction mechanisms allow the truthful elicitation of private signals (e.g., experiences, or ...
The modern web critically depends on aggregation of information from self-interested agents, for exa...
We study learning statistical properties from strategic agents with private information. In this pro...
textabstractFinancial markets reveal what investors think about the future, and prediction markets a...
In this dissertation, we analyze the interaction between intelligent and selfish agents in non-coope...
Abstract Peer-prediction mechanisms elicit information about unverifiable or subjective states of th...
In this paper, we propose a new mechanism - the Disagreement Mechanism - which elicits privately-hel...
Inferring the information structure of other agents is necessary to derive optimal mechanisms/signal...
We study a setting where Bayesian agents with a common prior have private information related to an ...
We outline how to create a mechanism that provides an optimal way to elicit, from an arbitrary group...
We consider a participatory sensing scenario where a group of private sensors observes the same phen...
The problem of peer prediction is to elicit information from agents in settings without any objectiv...
Integrating information gained by observing others via So-cial Bayesian Learning can be beneficial f...
Abstract. If a group as a whole is modelled as a single Bayesian agent, what should its beliefs be? ...