Although well understood in the single-agent framework, the use of traditional reinforcement learning (RL) algorithms in multi-agent systems (MAS) is not always justified. The fe...
We introduce a data structure for program execution under a limited oblivious execution model. For fully oblivious execution along the lines of Goldreich and Ostrovsky [2], one tr...
Avinash V. Varadarajan, Ramarathnam Venkatesan, C....
We study a refined framwork of parameterized complexity theory where the parameter dependendence of fixed-parameter tractable algorithms is not arbitrary, but restricted by a fu...
Recently, there has been an increased focus on modeling uncertainty by distributions. Suppose we wish to compute a function of a stream whose elements are samples drawn independen...
In this paper we propose a utility model that accounts for both sales and branding advertisers. We first study the computational complexity of optimization problems related to bo...