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.
11630076
Capacity allocation with competitive retailers
This paper addresses a problem in supply chain management that how scarce resources can be efficiently allocated among competing interests. We present a formal model of allocation mechanisms for such settings that a supplier with limited production capacity allocates its products to a set of competitive retailers. In contrary to the existing allocation mechanisms in which retailers are local monopolists, the new model exhibits much more complicated market behaviors. We show that the widely-used proportional allocation mechanism is no longer necessarily Pareto optimal, even if all retailers are in a symmetric situation. A necessary and sufficient condition for the proportional allocation to be Pareto optimal is given. We propose a truth-inducing allocation mechanism based on our capacity allocation model, which is more intuitive and applicable than the existing truth-inducing mechanisms.
15449547
Encoding Solutions of the Frame Problem in Dynamic Logic
We investigate the relationship amongst some solutions to the frame problem. We encode Pednault's syntax-based solution [20], Baker's state-minimization policy [1], and Gelfond & Lifchitz's Action Language A [7] in the propositional dynamic logic (PDL). The formal relationships among these solutions are given. The results of the paper show that dynamic logic, as one of the formalisms for reasoning about dynamic domains, can be used as a formal tool for comparing and unifying logics of action.
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.
35603840
State Minimization Re-visited
A well-known circumscription policy in situation calculus theories of actions is to minimize the Abnormality predicate by varying the Holds predicate. Unfortunately this admitted counter-intuitive models. A different policy of varying the Result function eliminated these models. Explanations of how it did this are not entirely satisfactory, but seem to appeal to informal notions of state minimization. We reexamine this policy and show that there are simple justifications for it that are based on classical automata theory. It incidentally turns out that the description "state minimization" for the varying Result policy is more accurate than the original nomenclature had intended.
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.
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.
16260947
A novel improvement to the R*-tree spatial index using gain/loss metrics
The R*-tree is a state-of-the-art spatial index structure. It has already found its way into commercial systems. The most important improvement of the R*-tree over the original R-tree is that it utilizes forced reinsertion. That is, if a disk page overflows, some objects are removed from the page and reinserted into the index. The goals are: (a) to reduce the MBR area; and (b) to keep the shape of the MBR close to a square. However, no existing work consists of a unified metric which can be used to balance the two criteria. For example, if there are two methods to remove objects from a rectangle, and one results in a rectangle with smaller area, while the other results in a square with slightly larger area, which method shall we choose? The R*-tree algorithm selects objects whose distances to the center of the page's MBR are the largest. However, this is not optimal. In this paper, we formally define the <i>quality</i> of a rectangle and the <i>gain</i> to shrink a rectangle. Then we provide algorithms to shrink the MBRs with the goal to maximize the gain. The algorithms are experimentally compared with the R*-tree's reinsertion algorithm. Furthermore, as the opposite of <i>gain</i>, we define the <i>loss</i> of expanding a rectangle. While inserting an object into the R*-tree, we need to choose a sub-tree to put the object in. With the new metric, we can choose the sub-tree with the least loss. Finally, we integrate the new algorithms into the R*-tree.
11522705
A supply chain network equilibrium model with random demands
Abstract In this paper, we develop a supply chain network model consisting of manufacturers and retailers in which the demands associated with the retail outlets are random. We model the optimizing behavior of the various decision-makers, derive the equilibrium conditions, and establish the finite-dimensional variational inequality formulation. We provide qualitative properties of the equilibrium pattern in terms of existence and uniqueness results and also establish conditions under which the proposed computational procedure is guaranteed to converge. Finally, we illustrate the model through several numerical examples for which the equilibrium prices and product shipments are computed. This is the first supply chain network equilibrium model with random demands for which modeling, qualitative analysis, and computational results have been obtained.
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.
34860384
Computer Simulation Study on Central Pattern Generator: from Biology to Engineering
Central pattern generator (CPG) is a neuronal circuit in the nervous system that can generate oscillatory patterns for the rhythmic movements. Its simplified format, neural oscillator, is wildly adopted in engineering application. This paper explores the CPG from an integral view that combines biology and engineering together. Biological CPG and simplified CPG are both studied. Computer simulation reveals the mechanism of CPG. Some properties, such as effect of tonic input and sensory feedback, stable oscillation, robustness, entrainment etc., are further studied. The promising results provide foundation for the potential engineering application in future.