A thesis submitted in conformity with the requirements

Recommender systems -- systems that suggest to users in e-commerce sites items that might interest them -- adopt a static view of the recommendation process and treat it as a prediction problem. In an earlier paper, we argued that it is more appropriate to view the problem of generating recommendations as a sequential decision problem and, consequently, that Markov decision processes (MDPs) provide a more appropriate model for recommender systems. MDPs introduce two benefits: they take into account the long-term effects of each recommendation, and they take into account the expected value of each recommendation. The use of MDPs in a commercial site raises three fundamental problems: providing an adequate initial model, updating this model online as new items (e.g., books) arrive, and coping with the enormous state-space of this model. In past work, we dealt with the first problem.

In this paper, we explore an architecture, called K-Trek, that enables mobile users to travel across knowledge distributed over a large geographical area (ranging from large public buildings to a national park). Our aim is providing, distributing, and enriching the environment with location-sensitive information for use by agents on board of mobile and static devices. Local interactions among KTrek devices and the distribution of information in the larger environment adopt some typical peer-to-peer patterns and techniques. We introduce the architecture, discuss some of its potential knowledge management applications, and present a few experimental results obtained with simulation.

Temporal logics are widely used in specifying goals of agents. We noticed that when directing agents, humans often revise their requirements for the agent, especially as they gather more knowledge about the domain. However, all existing temporal logics, except one, do not focus on the revision of goals in an elaboration tolerant manner. Thus formal temporal logics that can allow elaboration tolerant revision of goals are needed. As non-monotonic languages are often used for elaboration tolerant specification, we propose to explore non-monotonic temporal logics for goal specification. Recently, a non-monotonic temporal logic, N-LTL, was proposed with similar aims. In N-LTL, goal specifications could be changed via strong and weak exceptions. However, in N-LTL, one had to a-priori declare whether exceptions will be weak or strong exceptions. We propose a new non-monotonic temporal logic, that not only overcomes this, but is also able to express exception to exceptions, strengthen and weaken preconditions, and revise and replace consequents; all in an elaboration tolerant manner.

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