Traditional evaluation approaches are not sufficient to tackle the evaluation of web-based cooperative learning. Evaluation in this area is difficult because many factors influence the cooperative learning process, which are always changing. This makes it necessary to make adjustments to the cooperative tools and learning methods to fit particular settings and emerging requirements. Therefore, ...

Gradient descent learning algorithms have proven effective in solving mixed strategy games. The policy hill climbing (PHC) variants of WoLF (Win or Learn Fast) and PDWoLF (Policy Dynamics based WoLF) have both shown rapid convergence to equilibrium solutions by increasing the accuracy of their gradient parameters over standard Q-learning. Likewise, cooperative learning techniques using weighted...

A new optimization technique is proposed for classifiers fusion — Cooperative Coevolutionary Ensemble Learning (CCEL). It is based on a specific multipopulational evolutionary algorithm — cooperative coevolution. It can be used as a wrapper over any kind of weak algorithms, learning procedures and fusion functions, for both classification and regression tasks. Experiments on the real-world prob...

This paper explores a PAC (probably approximately correct) learning model in cooperative games. Specifically, we are given m random samples of coalitions and their values, taken from some unknown cooperative game; can we predict the values of unseen coalitions? We study the PAC learnability of several well-known classes of cooperative games, such as network flow games, threshold task games, and...

Cooperative/collaborative/team learning is an active learning technique in which students work and learn together in pairs or small groups to accomplish shared goals. The sites in this section offer information for faculty about getting started with instructional groups, designing group assignments, and using groups successfully. There is also a section designed for students, offering specific ...

We examinewhether student personality type helps explain differences in students’ course perceptions across sections that varied only in the usage of cooperative learning. We use theMyers Briggs Type Indicator to classify students based on their preferredways to take in information.We then compare the perceptions of students engaged in cooperative learning with perceptions of students engaged i...

Der Beitrag skizziert die CSCL-bezogenen Arbeiten unseres Forschungsschwerpunktes ubiquitäres Lernen. Er beschreibt insbesondere das DreiSchichten-Modell rechnergestützte Lernmittel – Lernobjekte – Lernstrategien. Einer der beiden Forschungsschwerpunkte des Fachgebiets Telekooperation ist ubiquitäres Lernen (uLearn). Mobile Endgeräte der Studierenden werden unterstützt und als Lernwerkzeug genu...

Cooperative/collaborative/team learning is an active learning technique in which students work and learn together in pairs or small groups to accomplish shared goals. The sites in this section offer information for faculty about getting started with instructional groups, designing group assignments, and using groups successfully. There is also a section designed for students, offering specific ...

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 learning in multiagent systems. We focus on multiagent systems where individual agents are capable of solving problems and learning using CBR (Case-based Reasoning). We present several collaboration strategies for age...

Learning in a dynamic, uncertain, multi-agent setting is a challenging task. In this work, we demonstrate techniques to convert noisy run-time activity into procedures useful for future problem-solving activities. The cooperative procedures created by this conversion process are stored in an agent resource called collective memory. We show how this memory enables agents to learn cooperative pro...