OBJECTIVE Approximately 66-80%of graduate students experience statistics anxiety and some researchers propose that many students identify statistics courses as the most anxiety-inducing courses in their academic curriculums. As such, it is likely that statistics anxiety is, in part, responsible for many students delaying enrollment in these courses for as long as possible. This paper proposes a...

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This paper examines, by argument, the dynamics of sequences of behavioural choices made, when non-cooperative restricted-memory agents learn in partially observable stochastic games. These sequences of combined agent strategies (joint-policies) can be thought of as a walk through the space of all possible joint-policies. We argue that this walk, while containing random elements, is also driven ...

Multi-Agent Learning (MAL) is a complex problem, especially in real-time systems where both cooperative and competitive learning are involved. We study this problem in the RoboCup Soccer KeepawayTakeaway game and propose Argumentation Accelerated Reinforcement Learning (AARL) for this game. AARL incorporates heuristics, represented by arguments in Value-Based Argumentation, into Reinforcement L...

In this work, we analyze the generalization ability of distributed online learning algorithms under stationary and non-stationary environments. We derive bounds for the excess-risk attained by each node in a connected network of learners and study the performance advantage that diffusion strategies have over individual non-cooperative processing. We conduct extensive simulations to illustrate t...

To develop a computer system to support cooperative learning among distributed students; developers should consider the foundations of cooperative learning. This article examines the basic elements that make cooperation work and proposes a framework for such computer supported cooperative learning (CSCL) systems. This framework consists of five main components to support cooperative group struc...

Abstract The present study attempted to investigate the impact of cooperation versus collaboration on college students` reading ability. To fulfill the purpose of the study, 90 participants were chosen from among 140 by means of administering the Nelson Proficiency Test. They were divided into three groups: cooperative group, collaborative group, and control group. A fifty-item multiple-choice ...

Abstract The present study attempted to investigate the impact of cooperation versus collaboration on college students` reading ability. To fulfill the purpose of the study, 90 participants were chosen from among 140 by means of administering the Nelson Proficiency Test. They were divided into three groups: cooperative group, collaborative group, and control group. A fifty-item multiple-choice ...

Competitive learning approaches with penalization or cooperation mechanism have been applied to unsupervised data clustering due to their attractive ability of automatic cluster number selection. In this paper, we further investigate the properties of different competitive strategies and propose a novel learning algorithm called Cooperative and Penalized Competitive Learning (CPCL), which imple...

So far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is Particle Swarm Optimization (PSO). Prior some efforts by applying fuzzy logic for improving defects of PSO such as trapping in local optimums and early convergence has been done. Moreover to overcome the problem of i...