38243180
Information Acquisition from Multi-agent Resources
Rational agents, information systems and knowledge bases all share the property that they may become more effective by combining information from multiple sources. However, as was clearly indicated by the notorious "Judge puzzle" proposed by W. J. Schoenmakers in 1986, combining information from several sources is a dangerous operation. The resulting database may turn out to be inconsistent, or even worse: there are situations where the result is consistent but supports inferences which contradict the beliefs of all contributing agents. 
 
In this paper we investigate the possibilities and limitations of strategies for coping with this problem. Our first attempt tries to characterize those situations where information can be combined without risking the undesirable situation that some derivable proposition contradicts the beliefs of all agents involved. The resulting notion is called Absolute safety. It turns out however that for that case only trivial solutions exist. Consequently any non-trivial strategy must use information about the epistemic states of the agents involved. 
 
Subsequently we investigate less restrictive notions of safety. The more interesting ones involve not only propositions about the world but also epistemic information about the knowledge of the agents. This information can be formulated conveniently using the logic of belief dependence which has been designed by the first author, and which has been used previously for designing effectively computable belief revision procedures. 
 
The results characterizing the alternative safety notions generalize for this extended logic. We present a notion of restricted almost safety within this framework which describes the safety of combining information under the hypothesis that the contributing agents eventually would have exchanged their information among themselves. For this notion an explicit solution to the Judge puzzle is given.
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.
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.
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.
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.
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.
32544015
Belief revision for adaptive negotiation agents
Existing negotiation agents are primitive in terms of what they can learn and how responsive they are towards the changing negotiation contexts. These weaknesses can be alleviated if an expressive representation language is used to represent negotiation contexts and a sound inference mechanism is applied to reason about the preferential changes arising in these negotiation contexts. This paper illustrates a novel adaptive negotiation agent model, which is underpinned by the well-known AGM belief revision logic. Our preliminary experiments show that the performance of the belief-based adaptive negotiation agents is promising.
1799662
REVIEW: a real-time virtual walkthrough system
1. Real-time Virtual Walkthrough Data representing virtual environments (VEs) are getting increasingly large in order to better simulate real scenes. This poses interesting challenges to organize, store, and render the data for interactive navigation in VEs, or walkthrough. A large VE usually consists of thousands of 3D objects, each of which can be represented by hundreds of polygons, and may take thousands of megabytes of storage space. The amount of data is so large that it is impossible to store all of them in the main memory. Even for memory resident models, the graphics pipeline can become a bottleneck quickly with a large amount of data and slow down the rendering to an unacceptable frame rate for the walkthrough.
16942431
A graph model for E-commerce recommender systems
Information overload on the Web has created enormous challenges to customers selecting products for online purchases and to online businesses attempting to identify customers' preferences efficiently. Various recommender systems employing different data representations and recommendation methods are currently used to address these challenges. In this research, we developed a graph model that provides a generic data representation and can support different recommendation methods. To demonstrate its usefulness and flexibility, we developed three recommendation methods: direct retrieval, association mining, and high-degree association retrieval. We used a data set from an online bookstore as our research test-bed. Evaluation results showed that combining product content information and historical customer transaction information achieved more accurate predictions and relevant recommendations than using only collaborative information. However, comparisons among different methods showed that high-degree association retrieval did not perform significantly better than the association mining method or the direct retrieval method in our test-bed.
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.
15320041
Feature extraction of volume data based on multi-scale representation
In this paper, we present a novel algorithm that can detect and extract salient points as features in 3-D volume datasets. This algorithm extracts not only the locations of feature points, but also finds out the scales at which the features are most significant. It applies the scale-space theory by adaptively processing the input volume in a few discrete scales. The features points, as well as their scales, detected can be used for subsequent processing, such as content-based volume data authentication and content-based volume rendering.We have implemented the algorithm and tested its effectiveness on several volume datasets. Some optimization has also been done on time-consuming intermediate steps to speed up the feature detection process.