In this paper, we propose a new integration approach to simulate an Autonomous Virtual Agent's cognitive learning of a task for interactive Virtual Environment applications. Our research focuses on the behavioural animation of virtual humans capable of acting independently. Our contribution is important because we present a solution for fast learning with evolution. We propose the concept of a ...

How can educators empower and encourage their students to be more proactive, and give them the tools necessary to learn on their own, utilizing digital language learning resources in a culturally sensitive way? Described below is a project that introduced students to how technology and the Internet can empower the independent language learner. The goal was for the students to develop knowledge ...

A cognitive collaborative reinforcement learning algorithm (CCRL) that incorporates an advisor into the learning process is developed to improve supervised learning. An autonomous learner is enabled with a self awareness cognitive skill to decide when to solicit instructions from the advisor. The learner can also assess the value of advice, and accept or reject it. The method is evaluated for r...

The aim of this study is to examine the advantages of Mobile-Assisted Language Learning (MALL), especially vocabulary learning of English as a foreign or second language (L2) in terms of the two strands: automatization and learner autonomy. Previous studies articulate that technology-enhanced L2 learning could bring about some positive effects. The use of technological functions in a mobile dev...

In recent years, the autonomous mobile robot has found diverse applications such as home/health care system, surveillance system in civil and military applications and exhibition robot. For surveillance tasks such as moving target pursuit or following and patrol in a region using mobile robot, this paper presents a fuzzy Q-learning, as an intelligent control for cost-based navigation, for auton...

Two studies tested self-determination theory with 2nd-year medical students in an interviewing course. Study 1 revealed that (a) individuals with a more autonomous orientation on the General Causality Orientation Scale had higher psychosocial beliefs at the beginning of the course and reported more autonomous reasons for participating in the course, and (b) students who perceived their instruct...

While many learning algorithms as well as dynamic growing and pruning techniques are appropriate for most technical applications, they do not work appropriately in the context of autonomous agents. Autonomous agents potentially operate in dynamically changing environments. They receive an endless data stream, which makes it impossible to store a fixed set of training patterns. Therefore, autono...

Reinforcement learning is an approach for learning optimal action policy via experiencing, i.e. using observed reward in environment states. Reinforcement learning algorithms include adaptive dynamic programming, temporal difference learning and Q-learning[1]. Examples of successful applications of reinforcement learning are controller for sustained inverted flight on an autonomous helicopter [...

In this paper, we rst propose a new continuous action learning automaton which uses a stochastic estimator learning algorithm to increase the speed of convergence. Then we introduce an adaptive and autonomous call admission algorithm, which uses the proposed learning automaton. The proposed algorithm minimizes blocking probability of new calls subject to constraint on dropping probability of ha...

We introduce CARLA, an open-source simulator for autonomous driving research. CARLA has been developed from the ground up to support development, training, and validation of autonomous urban driving systems. In addition to open-source code and protocols, CARLA provides open digital assets (urban layouts, buildings, vehicles) that were created for this purpose and can be used freely. The simulat...