A fundamental open problem in computational learning theory is whether there is an attribute efficient learning algorithm for the concept class of decision lists (Rivest, 1987; Bl...
We study the computational complexity of some central analysis problems for One-Counter Markov Decision Processes (OC-MDPs), a class of finitely-presented, countable-state MDPs. O...
Tomas Brazdil, Vaclav Brozek, Kousha Etessami, Ant...
We construct a domain-theoretic calculus for Lipschitz and differentiable functions, which includes addition, subtraction and composition. We then develop a domaintheoretic versio...
Computational trust and reputation models have been recognized as one of the key technologies required to design and implement agent systems. These models manage and aggregate the...
Abstract. Coordination graphs offer a tractable framework for cooperative multiagent decision making by decomposing the global payoff function into a sum of local terms. Each age...