Building upon research on motivation theory, we provide insights on how video games can be framed as expert tools that naturally reconcile learning and fun, a worthy goal since st...
In this paper, we describe a novel bidding strategy that autonomous trading agents can use to participate in Continuous Double Auctions (CDAs). Our strategy is based on both short...
Perukrishnen Vytelingum, Dave Cliff, Nicholas R. J...
Reinforcement learning has been used for training game playing agents. The value function for a complex game must be approximated with a continuous function because the number of ...
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
We explore an application to the game of Go of a reinforcement learning approach based on a linear evaluation function and large numbers of binary features. This strategy has prov...