Abstract. An optimal probabilistic-planning algorithm solves a problem, usually modeled by a Markov decision process, by finding its optimal policy. In this paper, we study the k ...
Web archives play an important role in preserving our cultural heritage for future generations. When searching them, a serious problem arises from the fact that terminology evolve...
Klaus Berberich, Srikanta J. Bedathur, Mauro Sozio...
Reinforcement learning algorithms that use eligibility traces, such as Sarsa(λ), have been empirically shown to be effective in learning good estimated-state-based policies in pa...
This paper reports on a novel decentralised technique for planning agent schedules in dynamic task allocation problems. Specifically, we use a Markov game formulation of these pr...
Archie C. Chapman, Rosa Anna Micillo, Ramachandra ...
Many tasks can be described by sequences of actions that normally exhibit some form of structure and that can be represented by a grammar. This paper introduces FOSeq, an algorithm...