We study the computational complexity of finding maximum a posteriori configurations in Bayesian networks whose probabilities are specified by logical formulas. This approach leads to a fine grained study in which local information such as context-sensitive independence and determinism can be considered. It also allows us to characterize more precisely the jump from tractability to NP-hardness and beyond, and to consider the complexity introduced by evidence alone.

Recently, several Web-scale knowledge harvesting systems have been built, each of which is competent at extracting information from certain types of data (e.g., unstructured text, structured tables on the web, etc.). In order to determine the response to a new query posed to such systems (e.g., is sugar a healthy food?), it is useful to integrate opinions from multiple systems. If a response is desired within a specific time budget (e.g., in less than 2 seconds), then maybe only a subset of these resources can be queried. In this paper, we address the problem of knowledge integration for on-demand time-budgeted query answering. We propose a new method, AskWorld, which learns a policy that chooses which queries to send to which resources, by accommodating varying budget constraints that are available only at query (test) time. Through extensive experiments on real world datasets, we demonstrate AskWorld’s capability in selecting most informative resources to query within test-time constraints, resulting in improved performance compared to competitive baselines.

Goal Recognition is the task of inferring an actor's goals given some or all of the actor's observed actions. There is considerable interest in Goal Recognition for use in intelligent personal assistants, smart environments, intelligent tutoring systems, and monitoring user's needs. In much of this work, the actor's observed actions are compared against a generated library of plans. Recent work by Ramirez and Geffner makes use of AI planning to determine how closely a sequence of observed actions matches plans for each possible goal. For each goal, this is done by comparing the cost of a plan for that goal with the cost of a plan for that goal that includes the observed actions. This approach yields useful rankings, but is impractical for real-time goal recognition in large domains because of the computational expense of constructing plans for each possible goal. In this paper, we introduce an approach that propagates cost and interaction information in a plan graph, and uses this information to estimate goal probabilities. We show that this approach is much faster, but still yields high quality results.

This paper deals with the problem of packing two-dimensional objects of quite arbitrary shapes including in particular curved shapes (like ellipses) and assemblies of them. This problem arises in industry for the packaging and transport of bulky objects which are not individually packed into boxes, like car spare parts. There has been considerable work on packing curved objects but, most of the time, with specific shapes; one famous example being the circle packing problem. There is much less algorithm for the general case where different shapes can be mixed together. A successful approach has been proposed recently in Martinez et al. (T. Martinez, L. Vitorino, F. Fages, and A. Aggoun. On Solving Mixed Shapes Packing Problems by Continuous Optimization with the CMA Evolution Strategy. In Proceedings of the first BRICS countries congress on Computational Intelligence, 2013) and the algorithm we propose here is an extension of their work. Martinez et al. use a stochastic optimization algorithm with a fitness function that gives a violation cost and equals zero when objects are all packed. Their main idea is to define this function as a sum of n!/(2!(n-2)!) elementary functions that measure the overlapping between each pair of different objects. However, these functions are ad-hoc formulas. Designing ad-hoc formulas for every possible combination of object shapes can be a very tedious task, which dramatically limits the applicability of their approach. The aim of this paper is to generalize the approach by replacing the ad-hoc formulas with a numerical algorithm that automatically measures the overlapping between two objects. Then, we come up with a fully black-box packing algorithm that accept any kind of objects.

However, humans are proved to question: What is the connection between the arguments proposed behave differently, mixing rational and emotional by the participants of a debate and their emotional attitudes to guide their actions, and it has been status? Such question breaks down into the following subquestions: claimed that there exists a strong connection between (1) is the polarity of arguments and the relations the argumentation process and the emotions among them correlated with the polarity of the detected emotions?, felt by people involved in such process. In this paper, and (2) what is the relation between the kind and the we assess this claim by means of an experiment: amount of arguments proposed in a debate, and the mental during several debates people's argumentation engagement detected among the participants of the debate? in plain English is connected and compared to the emotions automatically detected from the participants. To answer these questions, we propose an empirical evaluation Our results show a correspondence between of the connection between argumentation and emotions.

Craig Knoblock (University of Southern California, USA) Hiroaki Kitano (Sony Computer Science Laboratories, Inc., Japan) Sebastian run (Stanford University, USA) Raj Reddy (Carnegie Mellon University, USA) Ramasamy Uthurusamy (General Motors Corporation, retired) Erik Sandewall (Linköping Universit...

List of committee members on the program committees of the IJCAI 2015 conference.

List of chairs of the 2015 IJCAI conference programs.

This is an exciting time to be an artificial intelligence researcher. AI technologies and applications have truly entered our everyday lives, with AI systems in use throughout society. Against this backdrop of AI’s remarkable success, the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI-2015), to be held in Buenos Aires, Argentina between 25 and 31 July 2015, is poised to break several records. This is the first time the flagship international AI conference has been held in South America, and the number of submissions to the technical program has reached an historical high. These proceedings collect some of the most exciting research taking place in AI today and offer a window into the future. The theme of this year’s conference is Artificial Intelligence and Arts. Being held in Argentina, the home of Tango, the conference will feature invited talks, performances, demos and a technical track dedicated to the exploration and celebration of AI’s growing role in the Arts, both in enriching and producing Arts and in injecting art into AI to make it an elegant and more accessible scientific discipline.

Fuzzy answer set programming (FASP) combines two declarative frameworks, answer set programming and fuzzy logic, in order to model reasoning by default over imprecise information. Several connectives are available to combine different expressions; in particular the Gödel and Lukasiewicz fuzzy connectives are usually considered, due to their properties. Although the Gödel conjunction can be easily eliminated from rule heads, we show through complexity arguments that such a simplification is infeasible in general for all other connectives. The paper analyzes a translation of FASP programs into satisfiability modulo theories (SMT), which in general produces quantified formulas because of the minimality of the semantics. Structural properties of many FASP programs allow to eliminate the quantification, or to sensibly reduce the number of quantified variables. Indeed, integrality constraints can replace recursive rules commonly used to force Boolean interpretations, and completion subformulas can guarantee minimality for acyclic programs with atomic heads. Moreover, head cycle free rules can be replaced by shifted subprograms, whose structure depends on the eliminated head connective, so that ordered completion may replace the minimality check if also Lukasiewicz disjunction in rule bodies is acyclic. The paper also presents and evaluates a prototype system implementing these translations. KEYWORDS: answer set programming, fuzzy logic, satisfiability modulo theories.