In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
— Legged robots can, in principle, traverse a large variety of obstacles and terrains. In this paper, we describe a successful application of reinforcement learning to the proble...
To transplant the six characteristics of traditional collaborative learning into the network collaborative learning environment, this paper proposes the design of an Internet coll...
Fu-Chien Kao, Chia-Wei Liu, Zhi-Hua Ji, Chia-Liang...
Today's society is largely connected and many real life applications lend themselves to be modeled as multi-agent systems. Although such systems as well as their models are d...
An agent population can be evolved in a complex environment to perform various tasks and optimize its job performance using Learning Classifier System (LCS) technology. Due to the...