Mechanism design is the study of preference aggregation protocols that work well in the face of self-interested agents. We present the first general-purpose techniques for automa...
Tuomas Sandholm, Vincent Conitzer, Craig Boutilier
For many problems there is only suf£cient prior information for a Bayesian decision maker to identify a class of possible prior distributions. In such cases it is of interest to ...
We explore the phenomena of subjective randomness as a case study in understanding how people discover structure embedded in noise. We present a rational account of randomness per...
How humans infer probable information from the limited observed data? How they are able to build on little knowledge about the context in hand? Is the human memory repeatedly const...
This paper reviews a class of methods to perform causal inference in the framework of a structural vector autoregressive model. We consider three different settings. In the first ...