Consider a distributed network with nodes arranged in a tree, and each node having a local value. We consider the problem of aggregating values (e.g., summing values) from all nod...
C. Greg Plaxton, Mitul Tiwari, Praveen Yalagandula
We show how a generic feature selection algorithm returning strongly relevant variables can be turned into a causal structure learning algorithm. We prove this under the Faithfuln...
Abstract— Q-learning is a technique used to compute an optimal policy for a controlled Markov chain based on observations of the system controlled using a non-optimal policy. It ...
This paper introduces design principles for modular Bayesian fusion systems which can (i) cope with large quantities of heterogeneous information and (ii) can adapt to changing co...
Gregor Pavlin, Patrick de Oude, Marinus Maris, Jan...
Multi-agent problem domains may require distributed algorithms for a variety of reasons: local sensors, limitations of communication, and availability of distributed computational...
Sean Luke, Keith Sullivan, Liviu Panait, Gabriel C...