In this paper we study the topic of CBR systems learning from observations in which those observations can be represented as stochastic policies. We describe a general framework wh...
Kellen Gillespie, Justin Karneeb, Stephen Lee-Urba...
An agent's trust decision strategy consists of the agent's policies for making trust-related decisions, such as who to trust, how trustworthy to be, what reputations to ...
Abstract— The prediction of the future states in MultiAgent Systems has been a challenging problem since the begining of MAS. Robotic soccer is a MAS environment in which the pre...
Abstract. We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal stra...
The aim of this research is to develop an adaptive agent based model of auction scenarios commonly used in auction theory to help understand how competitors in auctions reach equil...