Reinforcement learning (RL) agents improve through trial-and-error, but when reward is sparse and the agent cannot discover successful action sequences, learning stagnates. This has been a notable problem in training deep RL agents to perform web-based tasks, such as booking flights or replying to emails, where a single mistake can ruin the entire sequence of actions. A common remedy is to “war...

This paper reports on a large-scale study carried out in four settings that investigates the potential of the Web as a medium of language instruction, both to complement face-to-face teaching and as a stand-alone course. Data was collected by questionnaires and observational procedures to ascertain student perceptions of the usefulness of Web-based learning, their views on its advantages and di...

The slogan that information is power has undergone a slight change. Today, information updating is in the focus of interest. The largest source of information is the world-wide web. Fast search methods are in need for this enormous source. In this paper a hybrid architecture that combines soft support vector classification and reinforcement learning for value estimation is introduced for the ev...

For a web-based dynamic learning environment, personalized support for learners becomes more important. In order to achieve optimal efficiency in a learning process, individual learner's cognitive learning style should be taken into account. It is necessary to provide learners with an individualized learning support system. In this paper, a framework of web learning system based on genetic algo...

Host manipulation by parasites and parasitoids is a fascinating phenomenon within evolutionary ecology, representing an example of extended phenotypes. To elucidate the mechanism of host manipulation, revealing the origin and function of the invoked actions is essential. Our study focused on the ichneumonid spider ectoparasitoid Reclinervellus nielseni, which turns its host spider (Cyclosa arge...

A fast and efficient page ranking mechanism for web crawling and retrieval remains as a challenging issue. Recently, several link based ranking algorithms like PageRank, HITS and OPIC have been proposed. In this paper, we propose a novel recursive method based on reinforcement learning which considers distance between pages as punishment, called ‘‘DistanceRank’’ to compute ranks of web pages. T...

Indexing systems for the World Wide Web, such as Lycos and Alta Vista, play an essential role in making the Web useful and usable. These systems are based on Information Retrieval methods for indexing plain text documents, but also include heuristics for adjusting their document rankings based on the special HTML structure of Web documents. In this paper, we describe a wide range of such heuris...

This article reports classroom research on learners’ perspectives on Web-based instruction that utilizes the Blackboard course management system. The Webbased instruction aims to provide and support collaborative learning while fostering learners’ autonomy and accountability. The article also provides a description of the course design along with task-based activities. The results drawn from th...

We present a system for rapidly and easily building instructable and selfadaptive Web agents for information-retrieval and information-extraction tasks. Our Wisconsin Adaptive Web Assistant (Wawa) constructs a Web agent by accepting user preferences in form of instructions and adapting the agent’s behavior as it encounters new information. Wawa has two neural networks that are responsible for t...