When you think about how far and fast computer science has progressed in recent years, it's
not hard to conclude that a seven-year old handbook may fall a little short of the kind of …

A novel genetic algorithm is reported that is non-revisiting: It remembers every position that it
has searched before. An archive is used to store all the solutions that have been explored …

Deep reinforcement learning has shown remarkable success in the past few years. Highly
complex sequential decision making problems have been solved in tasks such as game …

In this paper we present TDLEAF (λ), a variation on the TD (λ) algorithm that enables it to be
used in conjunction with game-tree search. We present some experiments in which our …

In this paper we present TDLeaf (lambda), a variation on the TD (lambda) algorithm that
enables it to be used in conjunction with game-tree search. We present some experiments in …

Abstract SaaS (Software-as-a-Service) is a service model provided by cloud computing. It
has a high requirement for QoS (Quality of Software) due to its method of providing software …

Amazing breakthroughs in reinforcement learning have taken place. Computers teach
themselves to play Chess and Go and beat world champions. There is talk about expanding …

Recent advances in bandit tools and techniques for sequential learning are steadily
enabling new applications and are promising the resolution of a range of challenging …

Dynamic Programming provides a convenient and unified framework for studying many state
models used in AI but no algorithms for handling large spaces. Heuristic-search methods, on …

Computational grids have an enormous potential to provide compute power. However, this
power remains largely unexploited today for most applications, except trivially parallel …