5951691
ALX, an Action Logic for Agents with Bounded Rationality
Abstract We propose a modal action logic that combines ideas from H.A. Simon's bounded rationality , S. Kripke's possible world semantics , G.H. von Wright's preference logic , Pratt's dynamic logic , Stalnaker's minimal change and more recent approaches to update semantics . ALX (the x th action logic) is sound, complete and decidable, making it the first complete logic for two-place preference operators. ALX avoids important drawbacks of other action logics, especially the counterintuitive necessitation rule for goals (every theorem must be a goal) and the equally counterintuitive closure of goals under logical implication.
38873444
Logics for Belief Dependence
In this paper, we investigate the theoretical foundations of belief dependence in multiple agent environment, where agents may rely on someone else about their beliefs or knowledge. Several logics for belief dependence are introduced and studied. First of all, we try to formalize the problem of belief dependence in the framework of general epistemic logics, by which we will argue that general epistemic logic is not appropriate to formalize the problem of belief dependence. Then, based on an approach which is similar to Fagin and Halpern's general awareness logic, we present the second logic for belief dependence, which is called a syntactic approach. The third logic is an adapted possible world logic, where sub-beliefs are directly introduced in the models.
19558398
Gestures for Embodied Agents with Logic Programming
The paper discusses how distributed logic programming can be used to define and control the hand gestures of embodied agents in virtual worlds, by using the STEP language as an interface between the constructs of logic programming and the humanoid model defined in Virtual Reality Modelling Language (VRML). By using this framework, different gesture dictionaries can be defined and variants of a hand gesture, according to dynamically changing factors, can be generated on the fly. The approach is tested on the demanding demonstrator of conducting, providing experience, also on time performance of the animation.
13610294
Seeing is believing: A common sense theory of the adoption of perception-based beliefs
In this paper we present a formal common sense theory of the adoption of perception-based beliefs. We begin with a logical analysis of perception and then consider when perception should lead to belief change. Our theory is intended to apply to perception in humans and to perception in artificial agents at the level of the symbolic interface between a vision system and a belief system. In order to provide a context for our work we relate it to the emerging field of cognitive robotics, give an abstract architecture for an agent which is both embodied and capable of reasoning, and relate this to the concrete architectures of two vision-based surveillance systems.
14446666
Awareness, Negation and Logical Omniscience
General Epistemic Logics suffer from the problem of logical omniscience, which is that an agent's knowledge and beliefs are closed under implication. There have been many attempts to solve the problem of logical omniscience. However, according to our intuition, sometimes an agent's knowledge and beliefs are indeed closed under implication. Based on the notion of awareness, we introduce two kinds of negations: general negation and strong negation. Moreover, four kinds of implications, general implication, strong implication, weak implication, and semi-strong implication, are introduced to correspond with the two kinds of negations. In our logics of regular awareness, explicit beliefs are not necessarily closed under general implication, which means that agents are not logically omniscient. However, explicit beliefs are closed under strong implication and semi-strong implication, which captures an intuitive closure property of beliefs.
18313204
A taxonomy of web agents
We propose a taxonomy of Web agents, which encompasses agents that provide a text-based interface to, for example, information retrieval services as well as avatar-embodied guides that help visitors to navigate in virtual environments. Our taxonomy must be regarded as an instrument to delineate targets for research and the realization of prototype applications that demonstrate the usefulness of agent-based intelligence on the Web. In addition, we deploy our agent-taxonomy to establish the implications particular target applications have with respect to software architecture and computational resources.
5239541
Link prediction approach to collaborative filtering
Recommender systems can provide valuable services in a digital library environment, as demonstrated by its commercial success in book, movie, and music industries. One of the most commonly-used and successful recommendation algorithms is collaborative filtering, which explores the correlations within user-item interactions to infer user interests and preferences. However, the recommendation quality of collaborative filtering approaches is greatly limited by the data sparsity problem. To alleviate this problem we have previously proposed graph-based algorithms to explore transitive user-item associations. In this paper, we extend the idea of analyzing user-item interactions as graphs and employ link prediction approaches proposed in the recent network modeling literature for making collaborative filtering recommendations. We have adapted a wide range of linkage measures for making recommendations. Our preliminary experimental results based on a book recommendation dataset show that some of these measures achieved significantly better performance than standard collaborative filtering algorithms
1637377
XSTEP: a markup language for embodied agents
In this paper we propose an XML-based markup language. called XSTEP for embodied agents, based on the scripting language STEP. XSTEP is the XML-based successor of STEP. The scripting language STEP incorporates the formal semantics of dynamic logic, and has been implemented in the distributed logic programming language DLP, a tool for the implementation of 3D Web agents. In this paper we discuss the issues of markup language design for embodied agents and several aspects of the implementation and application of XSTEP.
7757717
A kernel autoassociator approach to pattern classification
Autoassociators are a special type of neural networks which, by learning to reproduce a given set of patterns, grasp the underlying concept that is useful for pattern classification. In this paper, we present a novel nonlinear model referred to as kernel autoassociators based on kernel methods. While conventional non-linear autoassociation models emphasize searching for the non-linear representations of input patterns, a kernel autoassociator takes a kernel feature space as the nonlinear manifold, and places emphasis on the reconstruction of input patterns from the kernel feature space. Two methods are proposed to address the reconstruction problem, using linear and multivariate polynomial functions, respectively. We apply the proposed model to novelty detection with or without novelty examples and study it on the promoter detection and sonar target recognition problems. We also apply the model to mclass classification problems including wine recognition, glass recognition, handwritten digit recognition, and face recognition. The experimental results show that, compared with conventional autoassociators and other recognition systems, kernel autoassociators can provide better or comparable performance for concept learning and recognition in various domains.
35430187
ITQS: an integrated transport query system
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage, and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. SIGMOD 2004 June 13-18, 2004, Paris, France. Copyright 2004 ACM 1-58113-859-8/04/06 . . . <5.00. '( )%* & 5 6 '( & . & = = & 5
1765097
Towards Scaleable Protein Structure Comparison and Database Search
Comparing protein structures in three dimensions is a computationally expensive process that makes a full scan of a protein against a library of known protein structures impractical. To reduce the cost, we can use an approximation of the three dimensional structure that allows protein comparison to be performed quickly to filter away dissimilar proteins. In this paper, we present a new algorithm, called SCALE, for protein structure comparison. In SCALE, a protein is represented as a sequence of secondary structure elements (SSEs) augmented with 3D structural properties such as the distances and angles between the SSEs. As such, the comparison between two proteins is reduced to a sequence alignment problem between their corresponding sequences of SSEs. The 3-D structural properties of the proteins contribute to the similarity score between the two sequences. We have implemented SCALE, and compared its performance against existing schemes. Our performance study shows that SCALE outperforms existing methods in terms of both efficiency and effectiveness (measured in terms of precision and recall). To avoid exhaustive search, an index based on the structural properties is also proposed. The index prunes away a considerable amount of dissimilar proteins given a query protein.