Collaboration with agents in VR environments

Virtual reality is gaining on importance in many fields – scientific simulation, training, therapy and also more and more in entertainment. All these applications require the human user to interact with virtual worlds inhabited by intelligent characters and to solve simulated or real problems. This thesis will present an integrated approach to simulated problem solving in virtual reality environments, with the emphasis on teamwork and the ability to control the simulations. A simulation framework satisfying these goals will be presented. A unified approach to the representation of semantic information in virtual environments based on predicate calculus will be introduced, including the representation of the world state, action semantics and basic axioms holding in the simulated world. Afterwards, the focus will be on the collaboration model based on task delegation and facilitator-centric architecture. A simple but efficient facilitator design will be presented. The issues of the collaborative problem solving will be examined. A new technique using propositional (STRIPS-like) planning with delegated actions and object-specific planning will be described. A control technique for virtual characters/objects will be detailed, enabling run-time exchange of control and control sharing over a virtual entity between multiple autonomous agents and/or human users. Finally, a set of case studies will be shown, illustrating the possible applications of the techniques developed and described in this dissertation

Statistical Extraction of Multilingual Natural Language Patterns for RDF Predicates: Algorithms and Applications

The Data Web has undergone a tremendous growth period. It currently consists of more then 3300 publicly available knowledge bases describing millions of resources from various domains, such as life sciences, government or geography, with over 89 billion facts. In the same way, the Document Web grew to the state where approximately 4.55 billion websites exist, 300 million photos are uploaded on Facebook as well as 3.5 billion Google searches are performed on average every day. However, there is a gap between the Document Web and the Data Web, since for example knowledge bases available on the Data Web are most commonly extracted from structured or semi-structured sources, but the majority of information available on the Web is contained in unstructured sources such as news articles, blog post, photos, forum discussions, etc. As a result, data on the Data Web not only misses a significant fragment of information but also suffers from a lack of actuality since typical extraction methods are time-consuming and can only be carried out periodically. Furthermore, provenance information is rarely taken into consideration and therefore gets lost in the transformation process. In addition, users are accustomed to entering keyword queries to satisfy their information needs. With the availability of machine-readable knowledge bases, lay users could be empowered to issue more specific questions and get more precise answers. In this thesis, we address the problem of Relation Extraction, one of the key challenges pertaining to closing the gap between the Document Web and the Data Web by four means. First, we present a distant supervision approach that allows finding multilingual natural language representations of formal relations already contained in the Data Web. We use these natural language representations to find sentences on the Document Web that contain unseen instances of this relation between two entities. Second, we address the problem of data actuality by presenting a real-time data stream RDF extraction framework and utilize this framework to extract RDF from RSS news feeds. Third, we present a novel fact validation algorithm, based on natural language representations, able to not only verify or falsify a given triple, but also to find trustworthy sources for it on the Web and estimating a time scope in which the triple holds true. The features used by this algorithm to determine if a website is indeed trustworthy are used as provenance information and therewith help to create metadata for facts in the Data Web. Finally, we present a question answering system that uses the natural language representations to map natural language question to formal SPARQL queries, allowing lay users to make use of the large amounts of data available on the Data Web to satisfy their information need

A Nearest-Neighbor Approach to Indicative Web Summarization

Through their role of content proxy, in particular on search engine result pages, Web summaries play an essential part in the discovery of information and services on the Web. In their simplest form, Web summaries are snippets based on a user-query and are obtained by extracting from the content of Web pages. The focus of this work, however, is on indicative Web summarization, that is, on the generation of summaries describing the purpose, topics and functionalities of Web pages. In many scenarios — e.g. navigational queries or content-deprived pages — such summaries represent a valuable commodity to concisely describe Web pages while circumventing the need to produce snippets from inherently noisy, dynamic, and structurally complex content. Previous approaches have identified linking pages as a privileged source of indicative content from which Web summaries may be derived using traditional extractive methods. To be reliable, these approaches require sufficient anchortext redundancy, ultimately showing the limits of extractive algorithms for what is, fundamentally, an abstractive task. In contrast, we explore the viability of abstractive approaches and propose a nearest-neighbors summarization framework leveraging summaries of conceptually related (neighboring) Web pages. We examine the steps that can lead to the reuse and adaptation of existing summaries to previously unseen pages. Specifically, we evaluate two Text-to-Text transformations that cover the main types of operations applicable to neighbor summaries: (1) ranking, to identify neighbor summaries that best fit the target; (2) target adaptation, to adjust individual neighbor summaries to the target page based on neighborhood-specific template-slot models. For this last transformation, we report on an initial exploration of the use of slot-driven compression to adjust adapted summaries based on the confidence associated with token-level adaptation operations. Overall, this dissertation explores a new research avenue for indicative Web summarization and shows the potential value, given the diversity and complexity of the content of Web pages, of transferring, and, when necessary, of adapting, existing summary information between conceptually similar Web pages

Special Libraries, November 1979

Volume 70, Issue 11https://scholarworks.sjsu.edu/sla_sl_1979/1008/thumbnail.jp

ABSTRACT The ACORN Multi-Agent System

is a distributed multi-agent architecture for the search, distribution and management of information in networks. ACORN utilizes the concept of ‘information as agent ’ together with an application of Stanley Milgram’s Small World Problem (the idea of Six Degrees of Separation) in order to route individual items of information around networks of people and agents. The ACORN ideal is to achieve a state where a web of users is created such that information distribution, queries and search, and browsing behaviour is encapsulated in a single adaptive architecture which learns community behaviour and knowledge in order to route agents to relevant destinations (users). This paper describes the ACORN architecture and its implementation. We introduce a novel idea of agent meeting places, or Cafés, to carry out community-based information sharing among mobile agents in ACORN. ACORN is compared with similar work, and evaluations of ACORN for information sharing among mobile agents are described. Applications of ACORN include Business to Business and Business to Consumer based e-Commerce solutions, virtual community creation and support systems, peer reviewing systems, and personalized directed information handling (search, dissemination and growth). Keywords Multi-Agent information architectures, autonomous agents, mobile agents, keyphrase matching, multi-agent architecture, community based information handling, e-Commerce. 1

The Cryptographic Imagination

Originally published in 1996. In The Cryptographic Imagination, Shawn Rosenheim uses the writings of Edgar Allan Poe to pose a set of questions pertaining to literary genre, cultural modernity, and technology. Rosenheim argues that Poe's cryptographic writing—his essays on cryptography and the short stories that grew out of them—requires that we rethink the relation of poststructural criticism to Poe's texts and, more generally, reconsider the relation of literature to communication. Cryptography serves not only as a template for the language, character, and themes of much of Poe's late fiction (including his creation, the detective story) but also as a "secret history" of literary modernity itself. "Both postwar fiction and literary criticism," the author writes, "are deeply indebted to the rise of cryptography in World War II." Still more surprising, in Rosenheim's view, Poe is not merely a source for such literary instances of cryptography as the codes in Conan Doyle's "The Dancing-Men" or in Jules Verne, but, through his effect on real cryptographers, Poe's writing influenced the outcome of World War II and the development of the Cold War. However unlikely such ideas sound, The Cryptographic Imagination offers compelling evidence that Poe's cryptographic writing clarifies one important avenue by which the twentieth century called itself into being. "The strength of Rosenheim's work extends to a revisionistic understanding of the entirety of literary history (as a repression of cryptography) and then, in a breathtaking shift of register, interlinks Poe's exercises in cryptography with the hyperreality of the CIA, the Cold War, and the Internet. What enables this extensive range of applications is the stipulated tension Rosenheim discerns in the relationship between the forms of the literary imagination and the condition of its mode of production. Cryptography, in this account, names the technology of literary production—the diacritical relationship between decoding and encoding—that the literary imagination dissimulates as hieroglyphics—the hermeneutic relationship between a sign and its content."—Donald E. Pease, Dartmouth Colleg