Although well understood in the single-agent framework, the use of traditional reinforcement learning (RL) algorithms in multi-agent systems (MAS) is not always justified. The fe...
We introduce relational temporal difference learning as an effective approach to solving multi-agent Markov decision problems with large state spaces. Our algorithm uses temporal ...
Dynamic scripting is a reinforcement learning algorithm designed specifically to learn appropriate tactics for an agent in a modern computer game, such as Neverwinter Nights. This...
Abstract. This paper proposes a decision support system for tactical air combat environment using a combination of unsupervised learning for clustering the data and an ensemble of ...
Abstract. The EENCL algorithm [1] automatically designs neural network ensembles for classification, combining global evolution with local search based on gradient descent. Two mec...