We study a model of observational learning in social networks in the presence of uncertainty about agents' type distributions. Each individual receives a private noisy signal ...
Daron Acemoglu, Munther A. Dahleh, Asuman E. Ozdag...
In this paper we study the constrained consensus problem, i.e. the problem of reaching a common point from the estimates generated by multiple agents that are constrained to lie in...
Moment computation is essential to the analysis of stochastic kinetic models of biochemical reaction networks. It is often the case that the moment evolution, usually the first and...
The distributed estimation of the number of active sensors in a network can be important for estimation and organization purposes. We propose a design methodology based on the foll...
We present the MotionBeam metaphor for character interaction with handheld projectors. Our work draws from the tradition of pre-cinema handheld projectors that use direct physical...
Karl D. D. Willis, Ivan Poupyrev, Takaaki Shirator...