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1、Design of Web Agents Inspired by Brain Research Maya Dimitrova1, Hiroaki Wagatsuma2, and Yoko Yamaguchi2 1 Institute of Control and System Research, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Block 2, P.O.Box 79, 1113 Sofia, Bulgaria dimitrovaicsr.bas.bg 2 Laboratory for Dynamics of Emerg
2、ent Intelligence, RIKEN BSI, Hirosawa, Wako-shi, Saitama 351-0198, Japan waga, yokoybrain.riken.jp Abstract. The paper presents an approach to combine knowledge from memory and brain sciences with information retrieval research in the design of Web agents. An information retrieval agent for classifi
3、cation of Web pages based on genre features is used. In developing the agent to adapt to users search preferences, a neuro-cognitive model of human episodic memory is employed. Our studies show that neuro-realistic models, capable of abstraction of meaningful fragments of knowledge, rather than snap
4、shots of the retrieved Web pages, are closer to the human way of interacting with the Web and can be used for optimization of agent performance. Keywords: information retrieval, Web genre, theta phase precession theory, episodic memory. 1 Introduction Usable Web agents have to be adaptive to the dem
5、ands of the users as well as to the constant dynamic change of Web knowledge. In a way, Web agents have to mimic the natural flow of human memory processing - to filter useful information and remember meaningful facts - in the context of the unceasing flow of new knowledge from the resources on the
6、Web. It is becoming essential that Web agents are able to predict future knowledge needs of the diversity of Web users based on their own the agents experience 1, 2. It has been proposed that artificial agents as an agent subgroup have autobiography in terms of the ability of “story-telling”, i.e. r
7、econstruction of their own past 1. The framework is applied to autonomous robot behavior. Web agents are similar to autonomous robots in many ways in terms of learning, remembering, planning, and decision-making. In this paper we outline a distinction between the navigational (automatic) and the aut
8、obiographical (cognitive) aspects of Web browsing on the part of the user, which makes the navigational analogy between the artificial and the human agents performance incomplete. Design of Web agents is also concerned with identifying lexical or linguistic features of Web genre (not just topic rele
9、vance) like, for example, expertise, detail, subjectivity, etc. that can be captured by automatically scanning/tokenizing html scripts and extracting meaningful information 3, 4, 5. In order to make the process more efficient and sufficiently fast, a lot of heuristically based knowledge is employed.
10、 In some cases, these heuristics are grounded in long-tradition research areas like rule-based reasoning, neural networks, linguistics and cognitive science. Our aim is to relate the derived heuristics closer to insights from recent memory and brain modeling studies. In the present study we have foc
11、used on the phenomenology of episodic memory, and on one facet of its contribution to the formation of human autobiographical memory in Web context the extraction of meaningful fragments from the search episodes and its relevance to optimization of Web agent performance. The theta phase precession t
12、heory of hippocampal memory is chosen among related models for its account of complex cognitive phenomena like object-context integration, single-trial learning and time-space contextualization 6, 7. The employed neuro-realistic model is capable of abstraction of meaningful fragments of knowledge, r
13、ather than snapshots of the retrieved Web pages, which makes it closer to the human way of interacting with the Web and is appropriate for information retrieval optimization. 2 Information Retrieval Studies based on Cognitive Heuristics One application area of the information retrieval studies and i
14、nformation extraction algorithms dealing with a variety of stylistic and genre features is the Semantic Web, where software agents are built to analyze, restructure, transform and display the information, which currently exists in human-readable form. The algorithms used for discovering regularities
15、 in the html script that are meaningful from a user-viewer perspective and capable of extracting structural and semantic meaning from the text are called wrappers. The term wrapper is first proposed in 8 and, by definition, is a set of “relatively simple information extraction procedures for semi-st
16、ructured resources like texts”. Since the amount of regularities is enormous and constantly changing in the Web pages, a wrapper is a learner and in many cases learning is based on exposing to examples to extract the inner data or linguistic/text model. Structural meaning is conveyed by domain ontologies, which can be both designer- given and user-modified. The process of wrapper construction is called wrapper induction, which can be either handcrafted
