16817999
Convergency of Learning Process
This paper presents a learning process analysis on stability of learning in light of iterated belief revision. We view a learning process as a sequential belief change procedure. A learning policy is sought to guarantee every learning process leads to a complete knowledge about the world if the newly accepted information is the true fact on the world. The policy allows an agent to abandon the knowledge it has learned but requires a relatively moderate attitude to new information. It is shown that if new information is not always accepted in an extremely skeptical attitude and the changes of belief degrees follow the criterion of minimal change, any learning process for learning truth will converge to a complete knowledge state.
1234389
Nonmonotonic Reasoning and Multiple Belief Revision
The aim of the present paper is to reveal the interrelation between general patterns of nonmonotonic reasoning and multiple belief revision. For this purpose we de ne a nonmonotonic inference frame in which individual inference rules have been proposed in the literature but their combination as a system has not been investigated. It is shown that such a system is so strong that almost all the rules (including the supracompactness) suggested for nonmonotonic inference relations in the literature hold in it. We prove that this nonmonotonic inference frame is strictly correspendent with multiple belief revision operation. On the basis of this result we analyse a speci c paradigm of defult theory which satis es all the rules under consideration and discuss limitations of methods based on consequence relations for the study of nonmonotonic reasoning.
8370711
Consistency of Action Descriptions
As a contribution to the metatheory of reasoning about actions, we present some characteristics of the consistency of action theories. Three levels of consistency are investigated for the evaluation of action descriptions: uniform consistency, consistency of formulas and regional consistency. The first two provide an intuitive resolution of problems of explanation conflicts and fluent dependency. The concept of regional consistency provides for a measure of ramification. A highly expressive form of action descriptions, the normal form, is introduced to facilitate this analysis. The relative satisfiability of the situation calculus is generalized to accommodate non-deterministic effects and ramifications.
9693532
Negotiation mechanism for TAC SCM component market
This paper presents a new negotiation mechanism and a new supplier model for Trading Agent Competition Supply Chain Management(TAC SCM). Under the new negotiation mechanism, an agent is allowed to negotiate with component suppliers on price, delivery date and supply quantity while a supplier can autonomously vary its production capacity with market demands and allocate its products to buyers through auction. A mathematical analysis is given to ensure the new negotiation mechanism and supplier model effectively solve the existing problems while keeping most good features of the original TAC SCM game model.
10744441
Autonomy of Autonomous Agents
Autonomy is one of the most notable attributes of agency, and this paper presents a formal framework for modelhng it. By representing the mental states of agents, we provide an analysis of some attributes of autonomy. In particular, we define three sorts of autonomous agents and examine their structure. We also outline features of higher autonomy. Our framework can be a basis for cleissifying hierarchies of autonomy of agency.
1042778
Axiomatic Analysis of Negotiation Protocols
This paper presents an axiomatic approach to negotiation protocol analysis. We consider a negotiation procedure as multiple stages of mutual belief revision. A set of postulates in AGM-style of belief revision are proposed to specify rational behavior of negotiation. An explicit construction of negotiation function is given in which negotiation process is viewed as the interaction of two iterated revision operations. As a result the proposed axiomatic system is proved to be consistent. Finally, we examine our approach with an instantiation of Rosenschein and Zlotkin’s Monotonic Concession Protocol of Negotiation.
206133548
An efficient algorithm to rank Web resources
Abstract How to rank Web resources is critical to Web Resource Discovery (Search Engine). This paper not only points out the weakness of current approaches, but also presents in-depth analysis of the multidimensionality and subjectivity of rank algorithms. From a dynamics viewpoint, this paper abstracts a user's Web surfing action as a Markov model. Based on this model, we propose a new rank algorithm. The result of our rank algorithm, which synthesizes the relevance, authority, integrativity and novelty of each Web resource, can be computed efficiently not by iteration but through solving a group of linear equations.
30422301
Web Taxonomy Integration Using Spectral Graph Transducer
We address the problem of integrating objects from a source taxonomy into a master taxonomy. This problem is not only currently pervasive on the web, but also important to the emerging semantic web. A straightforward approach to automating this process would be to train a classifier for each category in the master taxonomy, and then classify objects from the source taxonomy into these categories. Our key insight is that the availability of the source taxonomy data could be helpful to build better classifiers in this scenario, therefore it would be beneficial to do transductive learning rather than inductive learning, i.e., learning to optimize classification performance on a particular set of test examples. In this paper, we attempt to use a powerful transductive learning algorithm, Spectral Graph Transducer (SGT), to attack this problem. Noticing that the categorizations of the master and source taxonomies often have some semantic overlap, we propose to further enhance SGT classifiers by incorporating the affinity information present in the taxonomy data. Our experiments with real-world web data show substantial improvements in the performance of taxonomy integration.
18688530
Web taxonomy integration through co-bootstrapping
We address the problem of integrating objects from a source taxonomy into a master taxonomy. This problem is not only currently pervasive on the web, but also important to the emerging semantic web. A straightforward approach to automating this process would be to learn a classifier that can classify objects from the source taxonomy into categories of the master taxonomy. The key insight is that the availability of the source taxonomy data could be helpful to build better classifiers for the master taxonomy if their categorizations have some semantic overlap. In this paper, we propose a new approach, co-bootstrapping, to enhance the classification by exploiting such implicit knowledge. Our experiments with real-world web data show substantial improvements in the performance of taxonomy integration.
10487566
Progressive computation of the min-dist optimal-location query
This paper proposes and solves the min-dist optimal-location query in spatial databases. Given a set S of sites, a set O of weighted objects, and a spatial region Q, the min-dist optimal-location query returns a location in Q which, if a new site is built there, minimizes the average distance from each object to its closest site. This query can help a franchise (e.g. McDonald's) decide where to put a new store in order to maximize the benefit to its customers. To solve this problem is challenging, for there are theoretically infinite number of locations in Q, all of which could be candidates. This paper first provides a theorem that limits the number of candidate locations without losing the power to find exact answers. Then it provides a progressive algorithm that quickly suggests a location, tells the maximum error it may have, and keeps refining the result. When the algorithm finishes, the exact answer can be found. The intermediate result of early runs can be used to prune the search space for later runs. Crucial to the pruning technique are novel lower-bound estimators. The proposed algorithm, the effect of several optimizations, and the progressiveness are experimentally evaluated.
377260
Supporting complex queries on multiversion XML documents
Managing multiple versions of XML documents represents a critical requirement for many applications. Recently, there has been much work on supporting complex queries on XML data (e.g., regular path expressions, structural projections, etc.). In this article, we examine the problem of implementing efficiently such complex queries on multiversion XML documents. Our approach relies on a numbering scheme, whereby durable node numbers (DNNs) are used to preserve the order among the nodes of the XML tree while remaining invariant with respect to updates. Using the document's DNNs, we show that many complex queries are reduced to combinations of range version retrieval queries. We thus examine three alternative storage organizations/indexing schemes to efficiently evaluate range version retrieval queries in this environment. A thorough performance analysis is then presented to reveal the advantages of each scheme.