Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
A common challenge for agents in multiagent systems is trying to predict what other agents are going to do in the future. Such knowledge can help an agent determine which of its c...
Ensuring the correctness of computer systems used in lifecritical applications is very difficult. The most commonly used verification methods, simulation and testing, are not exha...
Partially observable Markov decision processes (POMDPs) allow one to model complex dynamic decision or control problems that include both action outcome uncertainty and imperfect ...
In this paper we introduce the regional consecutive leader election (RCLE) problem, which extends the classic leader election problem to the ever-changing environment of mobile ad-...
Hyun Chul Chung, Peter Robinson, Jennifer L. Welch