Partially Observable Markov Decision Process (POMDP) is a popular framework for planning under uncertainty in partially observable domains. Yet, the POMDP model is riskneutral in ...
In this paper, we propose an Active Learning (AL) framework for the Multi-Task Adaptive Filtering (MTAF) problem. Specifically, we explore AL approaches to rapidly improve an MTAF...
ompositionality of Round Abstraction Abstract Dan R. Ghica and Mohamed N. Menaa University of Birmingham, U.K. We revisit a technique called round abstraction as a solution to the ...
POMDPs and their decentralized multiagent counterparts, DEC-POMDPs, offer a rich framework for sequential decision making under uncertainty. Their computational complexity, howeve...
Christopher Amato, Daniel S. Bernstein, Shlomo Zil...
We address the problem of cyclic termgraph rewriting. We propose a new framework where rewrite rules are tuples of the form (L, R, , ) such that L and R are termgraphs representing...