As multiagent environments become more prevalent we need to understand how this changes the agent-based paradigm. One aspect that is heavily affected by the presence of multiple a...
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
The paper describes a decentralized peer-to-peer multi-agent learning method based on inductive logic programming and knowledge trading. The method uses first-order logic for model...
This paper analyzes the movements of the human body limbs (hands, feet and head) and center of gravity in order to detect simple actions such as walking, jumping and displacing an...
Agents will adopt different strategies in the multiagent systems. However, the strategies of agents may produce conflicts. While agents coordinate with each other in the operation...