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Journal articles on the topic 'Jain Sects'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

Jaini, Padmanabh S. "Jaina monks from Mathura: literary evidence for their identification on Kuṣāṇa sculptures". Bulletin of the School of Oriental and African Studies 58, № 3 (1995): 479–94. http://dx.doi.org/10.1017/s0041977x0001291x.

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Among the thousands of Jaina images found throughout India, those from Mathura produced during the Kuṣāṇa period are unique, for they alone contain representations of unclothed Jaina ascetics holding a single small piece of cloth in such a way as to cover their nudity. These curious figures cannot be identified with monks of the present-day Jaina sects of the Digambaras, who practise total nudity, or of the Śvetāmbaras, who wear two long pieces of unstitched white cloth wrapped around their bodies and occasionally a white blanket over their left shoulders. The veteran art-historian, the late D

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Granoff, Phyllis. "Dundas, Paul, History, Scripture and Controversy in a Medieval Jain Sect." Indo-Iranian Journal 53, no. 2 (2010): 170–74. http://dx.doi.org/10.1163/001972409x12645171001451.

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3

Banks, Marcus J. "Defining Division: An Historical Overview of Jain Social Organization." Modern Asian Studies 20, no. 3 (1986): 447–60. http://dx.doi.org/10.1017/s0026749x00007812.

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This paper briefly charts the progress and findings of European scholars approaching the issues of caste and sect in the Jain community over the last two centuries. Other authors have already discussed the European interest in Jain textual and philosophical issues, and while I touch on these briefly, my main concern is to outline Jain social organization, with particular reference to Swetambar communities in the north.

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Michelson, M., and C. A. Knoblock. "Constructing Reference Sets from Unstructured, Ungrammatical Text." Journal of Artificial Intelligence Research 38 (May 28, 2010): 189–221. http://dx.doi.org/10.1613/jair.2937.

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Vast amounts of text on the Web are unstructured and ungrammatical, such as classified ads, auction listings, forum postings, etc. We call such text posts. Despite their inconsistent structure and lack of grammar, posts are full of useful information. This paper presents work on semi-automatically building tables of relational information, called reference sets, by analyzing such posts directly. Reference sets can be applied to a number of tasks such as ontology maintenance and information extraction. Our reference-set construction method starts with just a small amount of background knowl

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Benisch, M., G. B. Davis, and T. Sandholm. "Algorithms for Closed Under Rational Behavior (CURB) Sets." Journal of Artificial Intelligence Research 38 (August 20, 2010): 513–34. http://dx.doi.org/10.1613/jair.3070.

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We provide a series of algorithms demonstrating that solutions according to the fundamental game-theoretic solution concept of closed under rational behavior (CURB) sets in two-player, normal-form games can be computed in polynomial time (we also discuss extensions to n-player games). First, we describe an algorithm that identifies all of a players best responses conditioned on the belief that the other player will play from within a given subset of its strategy space. This algorithm serves as a subroutine in a series of polynomial-time algorithms for finding all minimal CURB sets, one minima

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Eiter, T., M. Fink, T. Krennwallner, C. Redl, and P. Schüller. "Efficient HEX-Program Evaluation Based on Unfounded Sets." Journal of Artificial Intelligence Research 49 (February 26, 2014): 269–321. http://dx.doi.org/10.1613/jair.4175.

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HEX-programs extend logic programs under the answer set semantics with external computations through external atoms. As reasoning from ground Horn programs with nonmonotonic external atoms of polynomial complexity is already on the second level of the polynomial hierarchy, minimality checking of answer set candidates needs special attention. To this end, we present an approach based on unfounded sets as a generalization of related techniques for ASP programs. The unfounded set detection is expressed as a propositional SAT problem, for which we provide two different encodings and optimizations

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Zaffalon, Marco, and Enrique Miranda. "Axiomatising Incomplete Preferences through Sets of Desirable Gambles." Journal of Artificial Intelligence Research 60 (December 30, 2017): 1057–126. http://dx.doi.org/10.1613/jair.5230.

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We establish the equivalence of two very general theories: the first is the decision-theoretic formalisation of incomplete preferences based on the mixture independence axiom; the second is the theory of coherent sets of desirable gambles (bounded variables) developed in the context of imprecise probability and extended here to vector-valued gambles. Such an equivalence allows us to analyse the theory of incomplete preferences from the point of view of desirability. Among other things, this leads us to uncover an unexpected and clarifying relation: that the notion of `state independence'---the

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Nienhuys-Cheng, S. H. "Least Generalizations and Greatest Specializations of Sets of Clauses." Journal of Artificial Intelligence Research 4 (May 1, 1996): 341–63. http://dx.doi.org/10.1613/jair.259.

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The main operations in Inductive Logic Programming (ILP) are generalization and specialization, which only make sense in a generality order. In ILP, the three most important generality orders are subsumption, implication and implication relative to background knowledge. The two languages used most often are languages of clauses and languages of only Horn clauses. This gives a total of six different ordered languages. In this paper, we give a systematic treatment of the existence or non-existence of least generalizations and greatest specializations of finite sets of clauses in each of these si

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Roijers, Diederik Marijn, Shimon Whiteson, and Frans A. Oliehoek. "Computing Convex Coverage Sets for Faster Multi-objective Coordination." Journal of Artificial Intelligence Research 52 (March 31, 2015): 399–443. http://dx.doi.org/10.1613/jair.4550.

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In this article, we propose new algorithms for multi-objective coordination graphs (MO-CoGs). Key to the efficiency of these algorithms is that they compute a convex coverage set (CCS) instead of a Pareto coverage set (PCS). Not only is a CCS a sufficient solution set for a large class of problems, it also has important characteristics that facilitate more efficient solutions. We propose two main algorithms for computing a CCS in MO-CoGs. Convex multi-objective variable elimination (CMOVE) computes a CCS by performing a series of agent eliminations, which can be seen as solving a series of loc

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Son, T. C., E. Pontelli, and P. H. Tu. "Answer Sets for Logic Programs with Arbitrary Abstract Constraint Atoms." Journal of Artificial Intelligence Research 29 (August 13, 2007): 353–89. http://dx.doi.org/10.1613/jair.2171.

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In this paper, we present two alternative approaches to defining answer sets for logic programs with arbitrary types of abstract constraint atoms (c-atoms). These approaches generalize the fixpoint-based and the level mapping based answer set semantics of normal logic programs to the case of logic programs with arbitrary types of c-atoms. The results are four different answer set definitions which are equivalent when applied to normal logic programs. The standard fixpoint-based semantics of logic programs is generalized in two directions, called answer set by reduct and answer set by complemen

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De Cooman, G., and E. Miranda. "Irrelevant and independent natural extension for sets of desirable gambles." Journal of Artificial Intelligence Research 45 (December 23, 2012): 601–40. http://dx.doi.org/10.1613/jair.3770.

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The results in this paper add useful tools to the theory of sets of desirable gambles, a growing toolbox for reasoning with partial probability assessments. We investigate how to combine a number of marginal coherent sets of desirable gambles into a joint set using the properties of epistemic irrelevance and independence. We provide formulas for the smallest such joint, called their independent natural extension, and study its main properties. The independent natural extension of maximal coherent sets of desirable gambles allows us to define the strong product of sets of desirable gambles. Fin

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Fearnley, David L., L. Fearnley та J. W. Lamoreaux. "There are no n-point Fσ sets in Rm". Bulletin of the Australian Mathematical Society 72, № 3 (2005): 477–80. http://dx.doi.org/10.1017/s0004972700035309.

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We show that, for any positive integers n and m, if a set S ⊂ Rm intersects every m − 1 dimensional affine hyperplane in Rm in exactly n points, then S is not an Fσ set. This gives a natural extension to results of Khalid Bouhjar, Jan J. Dijkstra, and R. Daniel Mauldin, who have proven this result for the case when m = 2, and also Jan J. Dijkstra and Jan van Mill, who have shown this result for the case when n = m.

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Bettini, C., S. Mascetti, and X. S. Wang. "Supporting Temporal Reasoning by Mapping Calendar Expressions to Minimal Periodic Sets." Journal of Artificial Intelligence Research 28 (March 19, 2007): 299–348. http://dx.doi.org/10.1613/jair.2136.

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In the recent years several research efforts have focused on the concept of time granularity and its applications. A first stream of research investigated the mathematical models behind the notion of granularity and the algorithms to manage temporal data based on those models. A second stream of research investigated symbolic formalisms providing a set of algebraic operators to define granularities in a compact and compositional way. However, only very limited manipulation algorithms have been proposed to operate directly on the algebraic representation making it unsuitable to use the symbolic

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Eiter, Thomas, Michael Fink, and Daria Stepanova. "Computing Repairs of Inconsistent DL-Programs over EL Ontologies." Journal of Artificial Intelligence Research 56 (July 27, 2016): 463–515. http://dx.doi.org/10.1613/jair.5047.

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Description Logic (DL) ontologies and non-monotonic rules are two prominent Knowledge Representation (KR) formalisms with complementary features that are essential for various applications. Nonmonotonic Description Logic (DL) programs combine these formalisms thus providing support for rule-based reasoning on top of DL ontologies using a well-defined query interface represented by so-called DL-atoms. Unfortunately, interaction of the rules and the ontology may incur inconsistencies such that a DL-program lacks answer sets (i.e., models), and thus yields no information. This issue is addressed

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Maly, Jan, Miroslaw Truszczyński, and Stefan Woltran. "Preference Orders on Families of Sets - When Can Impossibility Results Be Avoided?" Journal of Artificial Intelligence Research 66 (December 27, 2019): 1147–97. http://dx.doi.org/10.1613/jair.1.11879.

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Lifting a preference order on elements of some universe to a preference order on subsets of this universe is often guided by postulated properties the lifted order should have. Well-known impossibility results pose severe limits on when such liftings exist if all non-empty subsets of the universe are to be ordered. The extent to which these negative results carry over to other families of sets is not known. In this paper, we consider families of sets that induce connected subgraphs in graphs. For such families, common in applications, we study whether lifted orders satisfying the well-studied

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Geist, C., and U. Endriss. "Automated Search for Impossibility Theorems in Social Choice Theory: Ranking Sets of Objects." Journal of Artificial Intelligence Research 40 (January 24, 2011): 143–74. http://dx.doi.org/10.1613/jair.3126.

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We present a method for using standard techniques from satisfiability checking to automatically verify and discover theorems in an area of economic theory known as ranking sets of objects. The key question in this area, which has important applications in social choice theory and decision making under uncertainty, is how to extend an agent's preferences over a number of objects to a preference relation over nonempty sets of such objects. Certain combinations of seemingly natural principles for this kind of preference extension can result in logical inconsistencies, which has led to a number of

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Wang, G., Q. Song, H. Sun, X. Zhang, B. Xu, and Y. Zhou. "A Feature Subset Selection Algorithm Automatic Recommendation Method." Journal of Artificial Intelligence Research 47 (May 15, 2013): 1–34. http://dx.doi.org/10.1613/jair.3831.

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Many feature subset selection (FSS) algorithms have been proposed, but not all of them are appropriate for a given feature selection problem. At the same time, so far there is rarely a good way to choose appropriate FSS algorithms for the problem at hand. Thus, FSS algorithm automatic recommendation is very important and practically useful. In this paper, a meta learning based FSS algorithm automatic recommendation method is presented. The proposed method first identifies the data sets that are most similar to the one at hand by the k-nearest neighbor classification algorithm, and the distance

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18

Bouges, Janie Casello. "Why the SEC's First Attempt at Hedge Fund Adviser Registration Failed." Journal of Alternative Investments 9, no. 3 (2006): 89–94. http://dx.doi.org/10.3905/jai.2006.670102.

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19

Delgrande, J. P., and R. Wassermann. "Horn Clause Contraction Functions." Journal of Artificial Intelligence Research 48 (November 12, 2013): 475–511. http://dx.doi.org/10.1613/jair.4031.

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In classical, AGM-style belief change, it is assumed that the underlying logic contains classical propositional logic. This is clearly a limiting assumption, particularly in Artificial Intelligence. Consequently there has been recent interest in studying belief change in approaches where the full expressivity of classical propositional logic is not obtained. In this paper we investigate belief contraction in Horn knowledge bases. We point out that the obvious extension to the Horn case, involving Horn remainder sets as a starting point, is problematic. Not only do Horn remainder sets have unde

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20

Pang, Guansong, Kai Ming Ting, David Albrecht, and Huidong Jin. "ZERO++: Harnessing the Power of Zero Appearances to Detect Anomalies in Large-Scale Data Sets." Journal of Artificial Intelligence Research 57 (December 29, 2016): 593–620. http://dx.doi.org/10.1613/jair.5228.

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This paper introduces a new unsupervised anomaly detector called ZERO++ which employs the number of zero appearances in subspaces to detect anomalies in categorical data. It is unique in that it works in regions of subspaces that are not occupied by data; whereas existing methods work in regions occupied by data. ZERO++ examines only a small number of low dimensional subspaces to successfully identify anomalies. Unlike existing frequency-based algorithms, ZERO++ does not involve subspace pattern searching. We show that ZERO++ is better than or comparable with the state-of-the-art anomaly detec

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21

Cao, Yongcan, and Huixin Zhan. "Efficient Multi-objective Reinforcement Learning via Multiple-gradient Descent with Iteratively Discovered Weight-Vector Sets." Journal of Artificial Intelligence Research 70 (January 20, 2021): 319–49. http://dx.doi.org/10.1613/jair.1.12270.

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   Solving multi-objective optimization problems is important in various applications where users are interested in obtaining optimal policies subject to multiple (yet often conflicting) objectives. A typical approach to obtain the optimal policies is to first construct a loss function based on the scalarization of individual objectives and then derive optimal policies that minimize the scalarized loss function. Albeit simple and efficient, the typical approach provides no insights/mechanisms on the optimization of multiple objectives due to the lack of ability to quantify th

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22

Halpern, J. Y. "Defining Relative Likelihood in Partially-Ordered Preferential Structures." Journal of Artificial Intelligence Research 7 (July 1, 1997): 1–24. http://dx.doi.org/10.1613/jair.391.

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Starting with a likelihood or preference order on worlds, we extend it to a likelihood ordering on sets of worlds in a natural way, and examine the resulting logic. Lewis earlier considered such a notion of relative likelihood in the context of studying counterfactuals, but he assumed a total preference order on worlds. Complications arise when examining partial orders that are not present for total orders. There are subtleties involving the exact approach to lifting the order on worlds to an order on sets of worlds. In addition, the axiomatization of the logic of relative likelihood in the ca

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Zöller, Marc-André, and Marco F. Huber. "Benchmark and Survey of Automated Machine Learning Frameworks." Journal of Artificial Intelligence Research 70 (January 27, 2021): 409–72. http://dx.doi.org/10.1613/jair.1.11854.

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Machine learning (ML) has become a vital part in many aspects of our daily life. However, building well performing machine learning applications requires highly specialized data scientists and domain experts. Automated machine learning (AutoML) aims to reduce the demand for data scientists by enabling domain experts to build machine learning applications automatically without extensive knowledge of statistics and machine learning. This paper is a combination of a survey on current AutoML methods and a benchmark of popular AutoML frameworks on real data sets. Driven by the selected frameworks f

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Bodirsky, M., and M. Hils. "Tractable Set Constraints." Journal of Artificial Intelligence Research 45 (December 31, 2012): 731–59. http://dx.doi.org/10.1613/jair.3747.

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Many fundamental problems in artificial intelligence, knowledge representation, and verification involve reasoning about sets and relations between sets and can be modeled as set constraint satisfaction problems (set CSPs). Such problems are frequently intractable, but there are several important set CSPs that are known to be polynomial-time tractable. We introduce a large class of set CSPs that can be solved in quadratic time. Our class, which we call EI, contains all previously known tractable set CSPs, but also some new ones that are of crucial importance for example in description logics.

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Halpern, J. Y. "Cox's Theorem Revisited." Journal of Artificial Intelligence Research 11 (December 1, 1999): 429–35. http://dx.doi.org/10.1613/jair.644.

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The assumptions needed to prove Cox's Theorem are discussed and examined. Various sets of assumptions under which a Cox-style theorem can be proved are provided, although all are rather strong and, arguably, not natural.

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Santana, Patricia Jimbo, Laura Lanzarini, and Aurelio F. Bariviera. "Fuzzy Classification Rules with FRvarPSO Using Various Methods for Obtaining Fuzzy Sets." Journal of Advances in Information Technology 11, no. 4 (2020): 233–40. http://dx.doi.org/10.12720/jait.11.4.233-240.

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Halpern, J. Y. "Conditional Plausibility Measures and Bayesian Networks." Journal of Artificial Intelligence Research 14 (June 1, 2001): 359–89. http://dx.doi.org/10.1613/jair.817.

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A general notion of algebraic conditional plausibility measures is defined. Probability measures, ranking functions, possibility measures, and (under the appropriate definitions) sets of probability measures can all be viewed as defining algebraic conditional plausibility measures. It is shown that algebraic conditional plausibility measures can be represented using Bayesian networks.

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Konidaris, George, Leslie Pack Kaelbling, and Tomas Lozano-Perez. "From Skills to Symbols: Learning Symbolic Representations for Abstract High-Level Planning." Journal of Artificial Intelligence Research 61 (January 31, 2018): 215–89. http://dx.doi.org/10.1613/jair.5575.

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We consider the problem of constructing abstract representations for planning in high-dimensional, continuous environments. We assume an agent equipped with a collection of high-level actions, and construct representations provably capable of evaluating plans composed of sequences of those actions. We first consider the deterministic planning case, and show that the relevant computation involves set operations performed over sets of states. We define the specific collection of sets that is necessary and sufficient for planning, and use them to construct a grounded abstract symbolic representat

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Chawla, N. V., and G. Karakoulas. "Learning From Labeled And Unlabeled Data: An Empirical Study Across Techniques And Domains." Journal of Artificial Intelligence Research 23 (March 1, 2005): 331–66. http://dx.doi.org/10.1613/jair.1509.

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There has been increased interest in devising learning techniques that combine unlabeled data with labeled data ? i.e. semi-supervised learning. However, to the best of our knowledge, no study has been performed across various techniques and different types and amounts of labeled and unlabeled data. Moreover, most of the published work on semi-supervised learning techniques assumes that the labeled and unlabeled data come from the same distribution. It is possible for the labeling process to be associated with a selection bias such that the distributions of data points in the labeled and unlab

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Wu, J., and R. Givan. "Automatic Induction of Bellman-Error Features for Probabilistic Planning." Journal of Artificial Intelligence Research 38 (August 30, 2010): 687–755. http://dx.doi.org/10.1613/jair.3021.

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Domain-specific features are important in representing problem structure throughout machine learning and decision-theoretic planning. In planning, once state features are provided, domain-independent algorithms such as approximate value iteration can learn weighted combinations of those features that often perform well as heuristic estimates of state value (e.g., distance to the goal). Successful applications in real-world domains often require features crafted by human experts. Here, we propose automatic processes for learning useful domain-specific feature sets with little or no human interv

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Jordan, P. W., and M. A. Walker. "Learning Content Selection Rules for Generating Object Descriptions in Dialogue." Journal of Artificial Intelligence Research 24 (July 1, 2005): 157–94. http://dx.doi.org/10.1613/jair.1591.

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A fundamental requirement of any task-oriented dialogue system is the ability to generate object descriptions that refer to objects in the task domain. The subproblem of content selection for object descriptions in task-oriented dialogue has been the focus of much previous work and a large number of models have been proposed. In this paper, we use the annotated COCONUT corpus of task-oriented design dialogues to develop feature sets based on Dale and Reiter's (1995) incremental model, Brennan and Clark's (1996) conceptual pact model, and Jordan's (2000b) intentional influences model, and use t

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Opitz, D., and R. Maclin. "Popular Ensemble Methods: An Empirical Study." Journal of Artificial Intelligence Research 11 (August 1, 1999): 169–98. http://dx.doi.org/10.1613/jair.614.

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An ensemble consists of a set of individually trained classifiers (such as neural networks or decision trees) whose predictions are combined when classifying novel instances. Previous research has shown that an ensemble is often more accurate than any of the single classifiers in the ensemble. Bagging (Breiman, 1996c) and Boosting (Freund & Shapire, 1996; Shapire, 1990) are two relatively new but popular methods for producing ensembles. In this paper we evaluate these methods on 23 data sets using both neural networks and decision trees as our classification algorithm. Our results clearly

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Wiebe, J. M., T. P. O'Hara, Thorsten Ohrstrom-Sandgren, and K. J. McKeever. "An Empirical Approach to Temporal Reference Resolution." Journal of Artificial Intelligence Research 9 (November 1, 1998): 247–93. http://dx.doi.org/10.1613/jair.523.

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Scheduling dialogs, during which people negotiate the times of appointments, are common in everyday life. This paper reports the results of an in-depth empirical investigation of resolving explicit temporal references in scheduling dialogs. There are four phases of this work: data annotation and evaluation, model development, system implementation and evaluation, and model evaluation and analysis. The system and model were developed primarily on one set of data, and then applied later to a much more complex data set, to assess the generalizability of the model for the task being performed. Man

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Ghosh, Supriyo, Pradeep Varakantham, Yossiri Adulyasak, and Patrick Jaillet. "Dynamic Repositioning to Reduce Lost Demand in Bike Sharing Systems." Journal of Artificial Intelligence Research 58 (February 27, 2017): 387–430. http://dx.doi.org/10.1613/jair.5308.

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Bike Sharing Systems (BSSs) are widely adopted in major cities of the world due to concerns associated with extensive private vehicle usage, namely, increased carbon emissions, traffic congestion and usage of nonrenewable resources. In a BSS, base stations are strategically placed throughout a city and each station is stocked with a pre-determined number of bikes at the beginning of the day. Customers hire the bikes from one station and return them at another station. Due to unpredictable movements of customers hiring bikes, there is either congestion (more than required) or starvation (fewer

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Lissovoi, Andrei, and Pietro S. Oliveto. "On the Time and Space Complexity of Genetic Programming for Evolving Boolean Conjunctions." Journal of Artificial Intelligence Research 66 (November 12, 2019): 655–89. http://dx.doi.org/10.1613/jair.1.11821.

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Genetic programming (GP) is a general purpose bio-inspired meta-heuristic for the evolution of computer programs. In contrast to the several successful applications, there is little understanding of the working principles behind GP. In this paper we present a performance analysis that sheds light on the behaviour of simple GP systems for evolving conjunctions of n variables (ANDn). The analysis of a random local search GP system with minimal terminal and function sets reveals the relationship between the number of iterations and the progress the GP makes toward finding the target function. Aft

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Dubois, D., H. Fargier, and H. Prade. "Ordinal and Probabilistic Representations of Acceptance." Journal of Artificial Intelligence Research 22 (July 1, 2004): 23–56. http://dx.doi.org/10.1613/jair.1265.

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An accepted belief is a proposition considered likely enough by an agent, to be inferred from as if it were true. This paper bridges the gap between probabilistic and logical representations of accepted beliefs. To this end, natural properties of relations on propositions, describing relative strength of belief are augmented with some conditions ensuring that accepted beliefs form a deductively closed set. This requirement turns out to be very restrictive. In particular, it is shown that the sets of accepted belief of an agent can always be derived from a family of possibility rankings of stat

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Bayer-Zubek, V., and T. G. Dietterich. "Integrating Learning from Examples into the Search for Diagnostic Policies." Journal of Artificial Intelligence Research 24 (August 1, 2005): 263–303. http://dx.doi.org/10.1613/jair.1512.

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This paper studies the problem of learning diagnostic policies from training examples. A diagnostic policy is a complete description of the decision-making actions of a diagnostician (i.e., tests followed by a diagnostic decision) for all possible combinations of test results. An optimal diagnostic policy is one that minimizes the expected total cost, which is the sum of measurement costs and misdiagnosis costs. In most diagnostic settings, there is a tradeoff between these two kinds of costs. This paper formalizes diagnostic decision making as a Markov Decision Process (MDP). The paper introd

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Micalizio, R., and P. Torasso. "Cooperative Monitoring to Diagnose Multiagent Plans." Journal of Artificial Intelligence Research 51 (September 19, 2014): 1–70. http://dx.doi.org/10.1613/jair.4339.

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Diagnosing the execution of a Multiagent Plan (MAP) means identifying and explaining action failures (i.e., actions that did not reach their expected effects). Current approaches to MAP diagnosis are substantially centralized, and assume that action failures are independent of each other. In this paper, the diagnosis of MAPs, executed in a dynamic and partially observable environment, is addressed in a fully distributed and asynchronous way; in addition, action failures are no longer assumed as independent of each other. The paper presents a novel methodology, named Cooperative Weak-Committed

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Deagustini, Cristhian Ariel D., Maria Vanina Martinez, Marcelo A. Falappa, and Guillermo R. Simari. "Datalog+- Ontology Consolidation." Journal of Artificial Intelligence Research 56 (August 30, 2016): 613–56. http://dx.doi.org/10.1613/jair.5131.

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Knowledge bases in the form of ontologies are receiving increasing attention as they allow to clearly represent both the available knowledge, which includes the knowledge in itself and the constraints imposed to it by the domain or the users. In particular, Datalog± ontologies are attractive because of their property of decidability and the possibility of dealing with the massive amounts of data in real world environments; however, as it is the case with many other ontological languages, their application in collaborative environments often lead to inconsistency related issues. In this paper w

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Berrar, D. "An Empirical Evaluation of Ranking Measures With Respect to Robustness to Noise." Journal of Artificial Intelligence Research 49 (February 17, 2014): 241–67. http://dx.doi.org/10.1613/jair.4136.

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Ranking measures play an important role in model evaluation and selection. Using both synthetic and real-world data sets, we investigate how different types and levels of noise affect the area under the ROC curve (AUC), the area under the ROC convex hull, the scored AUC, the Kolmogorov-Smirnov statistic, and the H-measure. In our experiments, the AUC was, overall, the most robust among these measures, thereby reinvigorating it as a reliable metric despite its well-known deficiencies. This paper also introduces a novel ranking measure, which is remarkably robust to noise yet conceptually simple

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Grossi, Davide, Emiliano Lorini, and Francois Schwarzentruber. "The Ceteris Paribus Structure of Logics of Game Forms." Journal of Artificial Intelligence Research 53 (May 27, 2015): 91–126. http://dx.doi.org/10.1613/jair.4666.

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The article introduces a ceteris paribus modal logic, called CP, interpreted on the equivalence classes induced by finite sets of propositional atoms. This logic is studied and then used to embed three logics of strategic interaction, namely atemporal STIT, the coalition logic of propositional control (CL−PC) and the starless fragment of the dynamic logic of propositional assignments (DL−PA). The embeddings highlight a common ceteris paribus structure underpinning the key operators of all these apparently very different logics and show, we argue, remarkable similarities behind some of the most

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Blockeel, H., L. Dehaspe, B. Demoen, G. Janssens, J. Ramon, and H. Vandecasteele. "Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs." Journal of Artificial Intelligence Research 16 (February 1, 2002): 135–66. http://dx.doi.org/10.1613/jair.924.

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Inductive logic programming, or relational learning, is a powerful paradigm for machine learning or data mining. However, in order for ILP to become practically useful, the efficiency of ILP systems must improve substantially. To this end, the notion of a query pack is introduced: it structures sets of similar queries. Furthermore, a mechanism is described for executing such query packs. A complexity analysis shows that considerable efficiency improvements can be achieved through the use of this query pack execution mechanism. This claim is supported by empirical results obtained by incorporat

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Jurewicz, Mateusz, and Leon Derczynski. "Set-to-Sequence Methods in Machine Learning: A Review." Journal of Artificial Intelligence Research 71 (August 12, 2021): 885–924. http://dx.doi.org/10.1613/jair.1.12839.

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Machine learning on sets towards sequential output is an important and ubiquitous task, with applications ranging from language modelling and meta-learning to multi-agent strategy games and power grid optimization. Combining elements of representation learning and structured prediction, its two primary challenges include obtaining a meaningful, permutation invariant set representation and subsequently utilizing this representation to output a complex target permutation. This paper provides a comprehensive introduction to the _eld as well as an overview of important machine learning methods tac

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Garcia, Laurent, Claire Lefèvre, Igor Stéphan, Odile Papini, and Éric Würbel. "A Semantic Characterization ASP Base Revision." Journal of Artificial Intelligence Research 66 (December 17, 2019): 989–1029. http://dx.doi.org/10.1613/jair.1.11451.

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The paper deals with base revision for Answer Set Programming (ASP). Base revision in classical logic is done by the removal of formulas. Exploiting the non-monotonicity of ASP allows one to propose other revision strategies, namely addition strategy or removal and/or addition strategy. These strategies allow one to define families of rule-based revision operators. The paper presents a semantic characterization of these families of revision operators in terms of answer sets. This semantic characterization allows for equivalently considering the evolution of syntactic logic programs and the evo

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Li, Y., P. Musilek, M. Reformat, and L. Wyard-Scott. "Identification of Pleonastic It Using the Web." Journal of Artificial Intelligence Research 34 (March 27, 2009): 339–89. http://dx.doi.org/10.1613/jair.2622.

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In a significant minority of cases, certain pronouns, especially the pronoun it, can be used without referring to any specific entity. This phenomenon of pleonastic pronoun usage poses serious problems for systems aiming at even a shallow understanding of natural language texts. In this paper, a novel approach is proposed to identify such uses of it: the extrapositional cases are identified using a series of queries against the web, and the cleft cases are identified using a simple set of syntactic rules. The system is evaluated with four sets of news articles containing 679 extrapositional ca

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Garapa, Marco, Eduardo Fermé, and Maurício Reis. "Credibility-limited Base Revision: New Classes and Their Characterizations." Journal of Artificial Intelligence Research 69 (November 28, 2020): 1023–75. http://dx.doi.org/10.1613/jair.1.12298.

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In this paper we study a kind of operator —known as credibility-limited base revisions— which addresses two of the main issues that have been pointed out to the AGM model of belief change. Indeed, on the one hand, these operators are defined on belief bases (rather than belief sets) and, on the other hand, they are constructed with the underlying idea that not all new information is accepted. We propose twenty different classes of credibility-limited base revision operators and obtain axiomatic characterizations for each of them. Additionally we thoroughly investigate the interrelations (in th

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Greco, S., I. Trubitsyna, and E. Zumpano. "On the Semantics of Logic Programs with Preferences." Journal of Artificial Intelligence Research 30 (December 10, 2007): 501–23. http://dx.doi.org/10.1613/jair.2371.

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This work is a contribution to prioritized reasoning in logic programming in the presence of preference relations involving atoms. The technique, providing a new interpretation for prioritized logic programs, is inspired by the semantics of Prioritized Logic Programming and enriched with the use of structural information of preference of Answer Set Optimization Programming. Specifically, the analysis of the logic program is carried out together with the analysis of preferences in order to determine the choice order and the sets of comparable models. The new semantics is compared with other app

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Siskind, J. M. "Grounding the Lexical Semantics of Verbs in Visual Perception using Force Dynamics and Event Logic." Journal of Artificial Intelligence Research 15 (August 1, 2001): 31–90. http://dx.doi.org/10.1613/jair.790.

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This paper presents an implemented system for recognizing the occurrence of events described by simple spatial-motion verbs in short image sequences. The semantics of these verbs is specified with event-logic expressions that describe changes in the state of force-dynamic relations between the participants of the event. An efficient finite representation is introduced for the infinite sets of intervals that occur when describing liquid and semi-liquid events. Additionally, an efficient procedure using this representation is presented for inferring occurrences of compound events, described with

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Patel-Schneider, P. F., and R. Sebastiani. "A New General Method to Generate Random Modal Formulae for Testing Decision Procedures." Journal of Artificial Intelligence Research 18 (April 1, 2003): 351–89. http://dx.doi.org/10.1613/jair.1166.

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The recent emergence of heavily-optimized modal decision procedures has highlighted the key role of empirical testing in this domain. Unfortunately, the introduction of extensive empirical tests for modal logics is recent, and so far none of the proposed test generators is very satisfactory. To cope with this fact, we present a new random generation method that provides benefits over previous methods for generating empirical tests. It fixes and much generalizes one of the best-known methods, the random CNF_[]m test, allowing for generating a much wider variety of problems, covering in principl

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Ginsberg, M. L. "GIB: Imperfect Information in a Computationally Challenging Game." Journal of Artificial Intelligence Research 14 (June 1, 2001): 303–58. http://dx.doi.org/10.1613/jair.820.

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This paper investigates the problems arising in the construction of a program to play the game of contract bridge. These problems include both the difficulty of solving the game's perfect information variant, and techniques needed to address the fact that bridge is not, in fact, a perfect information game. GIB, the program being described, involves five separate technical advances: partition search, the practical application of Monte Carlo techniques to realistic problems, a focus on achievable sets to solve problems inherent in the Monte Carlo approach, an extension of alpha-beta pruning from

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