—Reinforcement learning is a framework in which an agent can learn behavior without knowledge on a task or an environment by exploration and exploitation. Striking a balance betw...
Zhengqiao Ji, Q. M. Jonathan Wu, Maher A. Sid-Ahme...
This paper proposes a novel method to characterize the performance of autonomous agents in the Trading Agent Competition for Supply Chain Management (TAC-SCM). We create benchmark...
In multi-agent systems, social commitments are increasingly used to capture roles, social norms, the semantics of agent communication as well as other inter-agent dependencies. Th...
Philippe Pasquier, Roberto A. Flores, Brahim Chaib...
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 ...
Virtual environments are now becoming a promising new technology to be used in the development of interactive learning environments for children. Perhaps triggered by the success ...