The purpose of this study is to explore how student competition using the tit-for-tat strategy could be remedied with a minimum design change in order to support student to collabo...
Using unlabeled data to help supervised learning has become an increasingly attractive methodology and proven to be effective in many applications. This paper applies semi-supervi...
Agents that operate in a multi-agent system can benefit significantly from adapting to other agents while interacting with them. This work presents a general architecture for a ...
: Stakeholder search is a general framework for an extension to the improving on the competition approach paradigm for cooperative search that allows for additional individual goal...
Cooperation and learning are two ways in which an agent can improve its performance. Cooperative Multiagent Learning is a framework to analyze the tradeoff between cooperation and ...