9615548
Dynamic Belief Hierarchies
Typically some of an agent's beliefs are more reliable than others. Consequently we give a hierarchical definition of belief, according to which an agent's beliefs form a coherent hierarchy and new beliefs are defined with reference to it. We then show how preferential entailment can be used to formalize the persistence and revision of belief hierarchies, and discuss the the relationship between our theory and the AGM theory of belief revision.
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.
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.
1230191
3D agent-based virtual communities
In this paper we propose an approach to 3D agent-based virtual communities in which autonomous agents are participants in VRML-based virtual worlds to enhance the interaction with users or serve as intelligent navigation assistants. In addition, an agent communication language (ACL) is designed as a high-level communication facility, in particular for the realization of shared objects in virtual communities. As a typical example of 3D agent-based virtual communities, a VRML-based multi-user soccer game has been developed and implemented in the distributed logic programming language DLP. We discuss how DLP can be used for the implementation of 3D agent-based virtual communities.
62635072
Kernel autoassociator with applications to visual classification
Autoassociator is an important issue in concept learning, and the learned concept of a particular class can be used to distinguish the class from the others. For nonlinear autoassociation, This work presents a new model referred to as kernel autoassociator. Using kernel feature space as a potential nonlinear manifold, the model formulates the autoassociation as a special reconstruction problem from kernel feature space to input space. Two methods are developed to solve the problem. We evaluate the autoassociator with artificial data, and apply it to handwritten digit recognition and multiview face recognition, yielding positive experimental results.
3144439
Fast rendering of foveated volumes in wavelet-based representation
A foveated volume can be viewed as a blending of multiple regions, each with a different level of resolution. It can be efficiently represented in the wavelet domain by retaining a small number of wavelet coefficients. We exploit the arrangement of those wavelet coefficients to achieve fast volume rendering. The running time is O(n2+m), where n is the width of the rendered image, and m is the number of wavelet coefficients retained for the foveated volume. Our algorithm consists of two phases. The first phase is a fast reconstruction of the super-voxels from the wavelet coefficients, and the second phase renders the super-voxels by carefully tracking rays with different thickness in the super-voxels. No expensive preprocessing on the wavelet coefficients is required. Hence, it is possible to interactively modify different viewing parameters like the transfer functions. A potential application of our algorithm is in remote visualization of large volume data-sets.
34497095
3D Protein Structure Matching by Patch Signatures
For determining functionality dependencies between two proteins, both represented as 3D structures, it is an essential condition that they have one or more matching structural regions called patches. As 3D structures for proteins are large, complex and constantly evolving, it is computationally expensive and very time-consuming to identify possible locations and sizes of patches for a given protein against a large protein database. In this paper, we address a vector space based representation for protein structures, where a patch is formed by the vectors within the region. Based on our previews work, a compact representation of the patch named patch signature is applied here. A similarity measure of two patches is then derived based on their signatures. To achieve fast patch matching in large protein databases, a match-and-expand strategy is proposed. Given a query patch, a set of small k-sized matching patches, called candidate patches, is generated in match stage. The candidate patches are further filtered by enlarging k in expand stage. Our extensive experimental results demonstrate encouraging performances with respect to this biologically critical but previously computationally prohibitive problem.
14317741
Interactive 3D modeling using only one image
For virtual reality systems, modeling of 3D objects and scenes is important and challenging. In this paper, we present an image-based interactive 3D modeling framework consisting of three major modules: photogrammetric modeling, human interaction, and texture mapping. These three modules are not sequentially used and they are mixed in the whole modeling process. The major idea is to explore the use of images in interactive modeling systems to achieve the automation. In particular, the use of only one image is addressed. On one side, unlike the common fully interactive modeling framework, the users are not required to specify some low level details interactively which can be derived automatically from the image. On the other side, it still requires human interactions to do some high level tasks that the algorithms are difficult to perform automatically. We have implemented the framework and experimental results are good.
7343489
Feature difference analysis in video authentication system
In most video authentication systems, the difference between features of the original and received videos is often used to decide the authenticity. In this paper, by employing mutual information to represent the similarity between the original and received video frames, we theoretically analyze the relationship between the feature difference and the video distortion. The relationship we derived is applied to estimate the maximum allowable feature difference in a video authentication system and to show how the feature difference varies with quantization step. Experimental results demonstrate that the derived relationship is reasonable and helpful for designing a robust video authentication system.