1,725,399 research outputs found
Acquiring User Strategies and Preferences for Negotiating Agents: A Default Then Adjust Method
No full textA wide range of algorithms have been developed for various types of negotiating agents. In developing such algorithms the main focus has been on their efficiency and their effectiveness. However, this is only a part of the picture. Typically, agents negotiate on behalf of their owners and for this to be effective the agents must be able to adequately represent their owners’ strategies and preferences for negotiation. However, the process by which such knowledge is acquired is typically left unspecified. To address this problem, we undertook a study of how user information about negotiation tradeoff strategies and preferences can be captured. Specifically, we devised a novel default-then-adjust acquisition technique. In this, the system firstly does a structured interview with the user to suggest the attributes that the tradeoff could be made between, then it asks the user to adjust the suggested default tradeoff strategy by improving some attribute to see how much worse the attribute being traded off can be made while still being acceptable, and, finally, it asks the user to adjust the default preference on the tradeoff alternatives. This method is consistent with the principles of standard negotiation theory and to demonstrate its effectiveness we implemented a prototype system and performed an empirical evaluation in an accommodation renting scenario. The result of this evaluation indicates the proposed technique is helpful and efficient in accurately acquiring the users’ tradeoff strategies and preferences
Acquiring domain knowledge for negotiating agents: a case study
No full textIn this paper, we employ the fuzzy repertory table technique to acquire the necessary domain knowledge for software agents to act as sellers and buyers using a bilateral, multi-issue negotiation model that can achieve optimal results in semi-competitive environments. In this context, the seller's domain knowledge that need to be acquired is the rewards associated with the products and restrictions attached to their purchase. The buyer's domain knowledge that is acquired is the requirements and preferences on the desired products. The knowledge acquisition methods we develop involve constructing three fuzzy repertory tables and their associated distinctions matrixes. The first two are employed to acquire the seller agent's domain knowledge; and the third one is used, together with an inductive machine learning algorithm, to acquire the domain knowledge for the buyer agent
Ion transport model for large LArTPC
No full textHigh single photoelectron (SPE) rates have been recently observed in several large LArTPC detectors operating at the surface. These single photons are background that could limit the LArTPC capability for low energy physics. To understand the origin of the high SPE rate, we developed a model focusing on the slowly moving positive and negative ions (space charge) induced by the ionization of cosmic rays and electron attachment to impurities in LAr. Our model can predict the electric field distortion due to the presence of space charge that is well matched to measurements. More importantly, the model contains two new processes that contribute to producing photons from the interactions of the ions, which provide a plausible explanation for the observed high single PE rate
A hybrid model for sharing information between fuzzy, uncertain and default reasoning models in multi-agent systems
No full textThis paper develops a hybrid model which provides a unified framework for the following four kinds of reasoning: 1)Zadeh's fuzzy approximate reasoning; 2) Truth qualification uncertain reasoning with respect to fuzzy propositions; 3)fuzzy default reasoning (proposed, in this paper, as an extension of Reiter's default reasoning); and 4)truth- qualification uncertain default reasoning associated with fuzzy statements (developed in this paper to enrich fuzzy default reasoning with uncertain information). Our hybrid model has the following characteristics: 1) basic uncertainty is estimated in terms of words or phrases in natural language and basic propositions are fuzzy; 2) uncertainty, linguistically expressed, can be handled in default reasoning; and 3) the four kinds of reasoning models mentioned above and their combination models will be the special cases of our hybrid model. Moreover, our model allows the reasoning to be performed in the case in which the information is fuzzy, uncertain and partial. More importantly, the problems of sharing the information among heterogenous fuzzy, uncertain and default reasoning models can be solved efficiently by using our model. Given this, our framework can be used as a basis for information sharing and exchange in knowledge-based multi-agent systems for practical applications such as automated group negotiations. Actually, to build such a foundation is the motivation of this paper
Knowledge-based acquisition of tradeoff preferences of negotiating agents
No full textA wide range of algorithms have been developed for various types of automated egotiation. In developing such algorithms the main focus has been on their efficiency and their effectiveness. However, this is only part of the picture. Agents typically negotiate on behalf of their owners and for this to be effective the agent must be able to adequately represent the owners' preferences. However, the process by which such knowledge is acquired is typically left unspecified. To remove this shortcoming, we present a case study indicating how the knowledge for a particular negotiation algorithm can be acquired. More precisely, according to the analysis on the automated negotiation model, we identified that user trade-off preferences play a fundamental role in negotiation in general. This topic has been addressed little in the research area of user preference elicitation for general decision making problems as well. In a previous paper, we proposed an exhaustive method to acquire user trade-off preferences. In this paper, we developed another method to remove the limitation of the high user workload of the exhaustive method. Although we cannot say that it can exactly capture user trade-off preferences, it models the main commonalities of trade-off relations and re users' individualities as well
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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