The main topic addressed in this paper is how to help learners select some instructive hypermedia-based learning resources according to their learning contexts from the Web. Our approach is to provide a digital library for web-based learning called e-Learning Library, which includes learning resource repository, local indexing, and adaptive navigation support. This aims to promote their learning with diverse learning resources involving a certain topic.

Modeling of the user’s interests is one of the most important issues to support a user to gather information. Although there are several promising methods to infer the interests from the user’s browsing behavior, they assume that the interests are consistent during the information gathering. However, in browsing which is one of the most popular ways to gather information, the user’s interests are often strongly dependent on the local context of the browsing. This paper describes a method to model the user’s shifting interests from the browsing history. An information filtering method using the model of the interests has been implemented. We call it “context-sensitive filtering.” The results of an experimental evaluation, by real users’ browsing for an encyclopedia in CDROM format, are also reported.

The authors describe a method to interleave planning with execution in the dynamic world. The system interleaves planning with execution using the success probability, SP: likelihood that a plan is executed well. Elemental probabilities are assigned to operations' effects and irrelevant state descriptions. A partial plan is transformed into a Bayesian network and its SP is computed. An agent switches planning to execution when SP decreases less than an execution threshold. The authors made experiments in Tileworld and found optimal thresholds between reactivity and deliberation. This is a preliminary report for solving tradeoff between reactivity and deliberation.

No abstract available.

A generalized version of a set-theoretical measure for obtaining similarities between patterns with nonindependent attributes is presented. The dependence here is given by the pairwise correlation. Since the proposed measure needs no assumption of attribute independence, the resulting similarity values can reflect directly the relationships between the attributes.

The occurrence pattern of clusterings of keys is analyzed by use of the generating function. Probabilities of occurrences of several clustered patterns are given as the coefficients of generating functions. Moreover, the result when a key-to-address transformation of aK + b /mod c is performed on clustered keys is briefly discussed.