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  • Time-delayed Collective Flow Diffusion Models for Inferring Latent People Flow from Aggregated Data at Limited Locations
    Artif. Intell. (IF 6.628) Pub Date : 2020-11-20
    Yusuke Tanaka; Tomoharu Iwata; Takeshi Kurashima; Hiroyuki Toda; Naonori Ueda; Toshiyuki Tanaka

    The rapid adoption of wireless sensor devices has made it easier to record location information of people in a variety of spaces (e.g., exhibition halls). Location information is often aggregated due to privacy and/or cost concerns. The aggregated data we use as input consist of the numbers of incoming and outgoing people at each location and at each time step. Since the aggregated data lack tracking

    更新日期:2020-11-21
  • Evaluating local explanation methods on ground truth
    Artif. Intell. (IF 6.628) Pub Date : 2020-11-14
    Riccardo Guidotti

    Evaluating local explanation methods is a difficult task due to the lack of a shared and universally accepted definition of explanation. In the literature, one of the most common ways to assess the performance of an explanation method is to measure the fidelity of the explanation with respect to the classification of a black box model adopted by an Artificial Intelligent system for making a decision

    更新日期:2020-11-18
  • X*: Anytime Multi-Agent Path Finding for Sparse Domains using Window-Based Iterative Repairs
    Artif. Intell. (IF 6.628) Pub Date : 2020-11-17
    Kyle Vedder; Joydeep Biswas

    Real-world multi-agent systems such as warehouse robots operate under significant time constraints – in such settings, rather than spending significant amounts of time solving for optimal paths, it is instead preferable to find valid, collision-free paths quickly, even if suboptimal, and given additional time, to iteratively refine such paths to improve their cost. In such domains, we observe that

    更新日期:2020-11-17
  • Mis- and disinformation in a bounded confidence model
    Artif. Intell. (IF 6.628) Pub Date : 2020-11-09
    Igor Douven; Rainer Hegselmann

    The bounded confidence model has been widely used to formally study groups of agents who are sharing opinions with those in their epistemic neighborhood. We revisit the model with an eye toward studying mis- and disinformation campaigns, which have been much in the news of late. To that end, we introduce typed agents into the model, specifically agents who can be irresponsible in different ways, most

    更新日期:2020-11-16
  • Dependency-based syntax-aware word representations
    Artif. Intell. (IF 6.628) Pub Date : 2020-11-16
    Meishan Zhang; Zhenghua Li; Guohong Fu; Min Zhang

    Dependency syntax has been demonstrated highly useful for a number of natural language processing (NLP) tasks. Typical approaches of utilizing dependency syntax include Tree-RNN and Tree-Linearization, both of which exploit explicit 1-best tree outputs from a well-trained parser as inputs. However, these approaches may suffer from error propagation due to the inevitable errors contained in the 1-best

    更新日期:2020-11-16
  • Selecting goals in oversubscription planning using relaxed plans
    Artif. Intell. (IF 6.628) Pub Date : 2020-11-04
    Angel García-Olaya; Tomás de la Rosa; Daniel Borrajo

    Planning deals with the task of finding an ordered set of actions that achieves some goals from an initial state. In many real-world applications it is unfeasible to find a plan achieving all goals due to limitations in the available resources. A common case consists of having a bound on a given cost measure that is less than the optimal cost needed to achieve all goals. Oversubscription planning (OSP)

    更新日期:2020-11-12
  • Dynamically improved bounds bidirectional search
    Artif. Intell. (IF 6.628) Pub Date : 2020-11-09
    E.C. Sewell; S.H. Jacobson

    This paper presents a bidirectional search algorithm that dynamically improves the bounds during its execution. It has the property that it always terminates on or before the forward search meets the backward search. Computational experiments on the pancake problem, the sliding tile puzzle, and the topspin problem demonstrate that it is capable of solving problems using significantly fewer node expansions

    更新日期:2020-11-12
  • Using POMDPs for Learning Cost Sensitive Decision Trees
    Artif. Intell. (IF 6.628) Pub Date : 2020-11-11
    Shlomi Maliah; Guy Shani

    In classification, an algorithm learns to classify a given instance based on a set of observed attribute values. In many real world cases testing the value of an attribute incurs a cost. Furthermore, there can also be a cost associated with the misclassification of an instance. Cost sensitive classification attempts to minimize the expected cost of classification, by deciding after each observed attribute

    更新日期:2020-11-12
  • Stable Fractional Matchings
    Artif. Intell. (IF 6.628) Pub Date : 2020-11-06
    Ioannis Caragiannis; Aris Filos-Ratsikas; Panagiotis Kanellopoulos; Rohit Vaish

    We study a generalization of the classical stable matching problem that allows for cardinal preferences (as opposed to ordinal) and fractional matchings (as opposed to integral). In this cardinal setting, stable fractional matchings can have much larger social welfare than stable integral ones. Our goal is to understand the computational complexity of finding an optimal (i.e., welfare-maximizing) stable

    更新日期:2020-11-06
  • On fair price discrimination in multi-unit markets
    Artif. Intell. (IF 6.628) Pub Date : 2020-09-18
    Michele Flammini; Manuel Mauro; Matteo Tonelli

    Discriminatory pricing policies, even if often perceived as unfair, are widespread. In fact, pricing differences for the same item among different national markets are common, or forms of discrimination based on the time of purchase, like in tickets' sales. In this work, we propose a framework for capturing “fair” price discrimination policies that can be tolerated by customers, and study its application

    更新日期:2020-11-06
  • Robustness among multiwinner voting rules
    Artif. Intell. (IF 6.628) Pub Date : 2020-10-28
    Robert Bredereck; Piotr Faliszewski; Andrzej Kaczmarczyk; Rolf Niedermeier; Piotr Skowron; Nimrod Talmon

    We investigate how robust the results of committee elections are with respect to small changes in the input preference orders, depending on the voting rules used. We find that for typical rules the effect of making a single swap of adjacent candidates in a single preference order is either that (1) at most one committee member might be replaced, or (2) it is possible that the whole committee will be

    更新日期:2020-11-06
  • A reconstruction of multipreference closure
    Artif. Intell. (IF 6.628) Pub Date : 2020-10-12
    Laura Giordano; Valentina Gliozzi

    The paper describes a preferential approach for dealing with exceptions in KLM preferential logics, based on the rational closure. It is well known that rational closure does not allow an independent handling of inheritance of different defeasible properties of concepts. In this work, we consider an alternative closure construction, called Multi Preference closure (MP-closure), which has been first

    更新日期:2020-10-30
  • Protecting elections by recounting ballots
    Artif. Intell. (IF 6.628) Pub Date : 2020-10-16
    Edith Elkind; Jiarui Gan; Svetlana Obraztsova; Zinovi Rabinovich; Alexandros A. Voudouris

    Complexity of voting manipulation is a prominent topic in computational social choice. In this work, we consider a two-stage voting manipulation scenario. First, a malicious party (an attacker) attempts to manipulate the election outcome in favor of a preferred candidate by changing the vote counts in some of the voting districts. Afterwards, another party (a defender), which cares about the voters'

    更新日期:2020-10-30
  • Pruning external minimality checking for answer set programs using semantic dependencies
    Artif. Intell. (IF 6.628) Pub Date : 2020-10-16
    Thomas Eiter; Tobias Kaminski

    Answer set programming (ASP) has become an increasingly popular approach for declarative problem solving. In order to address the needs of applications, ASP has been extended in different approaches with means for interfacing the outside world, of which hex programs are one of the most powerful such extension that provides API-style interfaces to access arbitrary external sources of information and

    更新日期:2020-10-30
  • Evaluating XAI: A comparison of rule-based and example-based explanations
    Artif. Intell. (IF 6.628) Pub Date : 2020-10-28
    Jasper van der Waa; Elisabeth Nieuwburg; Anita Cremers; Mark Neerincx

    Current developments in Artificial Intelligence (AI) led to a resurgence of Explainable AI (XAI). New methods are being researched to obtain information from AI systems in order to generate explanations for their output. However, there is an overall lack of valid and reliable evaluations of the effects on user's experience and behaviour of explanations. New XAI methods are often based on an intuitive

    更新日期:2020-10-30
  • Quantifying controllability in temporal networks with uncertainty
    Artif. Intell. (IF 6.628) Pub Date : 2020-09-23
    Shyan Akmal; Savana Ammons; Hemeng Li; Michael Gao; Lindsay Popowski; James C. Boerkoel

    Controllability for Simple Temporal Networks with Uncertainty (STNUs) has thus far been limited to three levels: strong, dynamic, and weak. Because of this, there is currently no systematic way for an agent to assess just how far from being controllable an uncontrollable STNU is. We provide new insights inspired by a geometric interpretation of STNUs to introduce the degrees of strong and dynamic controllability

    更新日期:2020-10-13
  • On composition of bounded-recall plans
    Artif. Intell. (IF 6.628) Pub Date : 2020-10-07
    Kaya Deuser; Pavel Naumov

    The article studies the ability of agents with bounded memory to execute consecutive composition of plans. It gives an upper limit on the amount of memory required to execute the composed plans and shows that the limit cannot be improved. Furthermore, the article shows that there are, essentially, no other universal properties of plans for bounded-recall agents expressible through the relation “there

    更新日期:2020-10-13
  • Understanding the power of Max-SAT resolution through UP-resilience
    Artif. Intell. (IF 6.628) Pub Date : 2020-10-06
    Mohamed Sami Cherif; Djamal Habet; André Abramé

    A typical Branch and Bound algorithm for Max-SAT computes the lower bound by estimating the number of disjoint Inconsistent Subsets (IS) of the formula. The IS detection is ensured by Simulated Unit Propagation (SUP). Then, the inference rule for Max-SAT, Max-SAT resolution, is applied to ensure that the detected IS is counted only once. Learning Max-SAT resolution transformations can be detrimental

    更新日期:2020-10-11
  • SAT-based explicit LTLf satisfiability checking
    Artif. Intell. (IF 6.628) Pub Date : 2020-08-18
    Jianwen Li; Geguang Pu; Yueling Zhang; Moshe Y. Vardi; Kristin Y. Rozier

    Linear Temporal Logic over finite traces (LTLf) was proposed in 2013 and has attracted increasing interest around the AI community. Though the theoretic basis for LTLf has been thoroughly explored since that time, there are still few algorithmic tools that are able to provide an efficient reasoning strategy for LTLf. In this paper, we present a SAT-based framework for LTLf satisfiability checking,

    更新日期:2020-09-30
  • Real-time reasoning in OWL2 for GDPR compliance
    Artif. Intell. (IF 6.628) Pub Date : 2020-09-18
    Piero A. Bonatti; Luca Ioffredo; Iliana M. Petrova; Luigi Sauro; Ida R. Siahaan

    This paper shows how knowledge representation and reasoning techniques can be used to support organizations in complying with the GDPR, that is, the new European data protection regulation. This work is carried out in a European H2020 project called SPECIAL. Data usage policies, the consent of data subjects, and selected fragments of the GDPR are encoded in a fragment of OWL2 called PL (policy language);

    更新日期:2020-09-24
  • Explanation in AI and law: Past, present and future
    Artif. Intell. (IF 6.628) Pub Date : 2020-09-16
    Katie Atkinson; Trevor Bench-Capon; Danushka Bollegala

    Explanation has been a central feature of AI systems for legal reasoning since their inception. Recently, the topic of explanation of decisions has taken on a new urgency, throughout AI in general, with the increasing deployment of AI tools and the need for lay users to be able to place trust in the decisions that the support tools are recommending. This paper provides a comprehensive review of the

    更新日期:2020-09-23
  • Intrinsic approaches to prioritizing diagnoses in multi-context systems
    Artif. Intell. (IF 6.628) Pub Date : 2020-09-14
    Kedian Mu

    Multi-context systems introduced by Brewka and Eiter provide a promising framework for interlinking heterogeneous and autonomous knowledge sources. The notion of diagnosis has been proposed for analyzing inconsistency in multi-context systems, which captures a pair of subsets of bridge rules of a multi-context system needed to be deactivated and activated unconditionally, respectively, in order to

    更新日期:2020-09-22
  • So, what exactly is a qualitative calculus?
    Artif. Intell. (IF 6.628) Pub Date : 2020-09-14
    Armen Inants; Jérôme Euzenat

    The paradigm of algebraic constraint-based reasoning, embodied in the notion of a qualitative calculus, is studied within two alternative frameworks. One framework defines a qualitative calculus as “a non-associative relation algebra (NA) with a qualitative representation”, the other as “an algebra generated by jointly exhaustive and pairwise disjoint (JEPD) relations”. These frameworks provide complementary

    更新日期:2020-09-18
  • Dashed strings for string constraint solving
    Artif. Intell. (IF 6.628) Pub Date : 2020-09-05
    Roberto Amadini; Graeme Gange; Peter J. Stuckey

    String processing is ubiquitous across computer science, and arguably more so in web programming — where it is also a critical part of security issues such as injection attacks. In recent years, a number of string solvers have been developed to solve combinatorial problems involving string variables and constraints. We examine the dashed string approach to string constraint solving, which represents

    更新日期:2020-09-10
  • Autoepistemic answer set programming
    Artif. Intell. (IF 6.628) Pub Date : 2020-09-01
    Pedro Cabalar; Jorge Fandinno; Luis Fariñas del Cerro

    Defined by Gelfond in 1991, epistemic specifications constitute an extension of Answer Set Programming (ASP) that introduces subjective literals. A subjective literal allows checking whether some regular literal is true in all (or in some of) the answer sets of the program, that are further collected in a set called world view. One epistemic program may yield several world views but, under the original

    更新日期:2020-09-10
  • When security games hit traffic: A deployed optimal traffic enforcement system
    Artif. Intell. (IF 6.628) Pub Date : 2020-09-01
    Ariel Rosenfeld; Oleg Maksimov; Sarit Kraus

    Road accidents are the leading causes of death among youths and young adults worldwide. Efficient traffic enforcement is an essential, yet complex, component in preventing road accidents. In this article, we present a novel model, an optimizing algorithm and a deployed system which together mitigate many of the computational and real-world challenges of traffic enforcement allocation in large road

    更新日期:2020-09-05
  • Probability pooling for dependent agents in collective learning
    Artif. Intell. (IF 6.628) Pub Date : 2020-08-19
    Jonathan Lawry; Chanelle Lee

    The use of copulas is proposed as a way of modelling dependencies between different agents' probability judgements when carrying out probability pooling. This is combined with an established Bayesian model in which pooling is viewed as a form of updating on the basis of probability values provided by different individuals. Adopting the Frank family of copulas we investigate the effect of different

    更新日期:2020-08-24
  • Fixed point semantics for stream reasoning
    Artif. Intell. (IF 6.628) Pub Date : 2020-08-18
    Christian Antić

    Reasoning over streams of input data is an essential part of human intelligence. During the last decade stream reasoning has emerged as a research area within the AI-community with many potential applications. In fact, the increased availability of streaming data via services like Google and Facebook has raised the need for reasoning engines coping with data that changes at high rate. Recently, the

    更新日期:2020-08-22
  • Interestingness elements for explainable reinforcement learning: Understanding agents' capabilities and limitations
    Artif. Intell. (IF 6.628) Pub Date : 2020-08-12
    Pedro Sequeira; Melinda Gervasio

    We propose an explainable reinforcement learning (XRL) framework that analyzes an agent's history of interaction with the environment to extract interestingness elements that help explain its behavior. The framework relies on data readily available from standard RL algorithms, augmented with data that can easily be collected by the agent while learning. We describe how to create visual summaries of

    更新日期:2020-08-22
  • Knowledge-based programs as succinct policies for partially observable domains
    Artif. Intell. (IF 6.628) Pub Date : 2020-08-14
    Bruno Zanuttini; Jérôme Lang; Abdallah Saffidine; François Schwarzentruber

    We suggest to express policies for contingent planning by knowledge-based programs (KBPs). KBPs, introduced by Fagin et al. (1995) [32], are high-level protocols describing the actions that the agent should perform as a function of their current knowledge: branching conditions are epistemic formulas that are interpretable by the agent. The main aim of our paper is to show that KBPs can be seen as a

    更新日期:2020-08-20
  • Utilitarian welfare and representation guarantees of approval-based multiwinner rules
    Artif. Intell. (IF 6.628) Pub Date : 2020-08-05
    Martin Lackner; Piotr Skowron

    To choose a suitable multiwinner voting rule is a hard and ambiguous task. Depending on the context, it varies widely what constitutes the choice of an “optimal” subset of alternatives. In this paper, we provide a quantitative analysis of multiwinner voting rules using methods from the theory of approximation algorithms—we estimate how well multiwinner rules approximate two extreme objectives: a representation

    更新日期:2020-08-12
  • Price of Pareto Optimality in hedonic games
    Artif. Intell. (IF 6.628) Pub Date : 2020-07-27
    Edith Elkind; Angelo Fanelli; Michele Flammini

    The Price of Anarchy measures the welfare loss caused by selfish behavior: it is defined as the ratio of the social welfare in a socially optimal outcome and in a worst Nash equilibrium. Similar measures can be derived for other classes of stable outcomes. We observe that Pareto optimality can be seen as a notion of stability: an outcome is Pareto optimal if and only if it does not admit a deviation

    更新日期:2020-08-05
  • Negotiating team formation using deep reinforcement learning
    Artif. Intell. (IF 6.628) Pub Date : 2020-07-25
    Yoram Bachrach; Richard Everett; Edward Hughes; Angeliki Lazaridou; Joel Z. Leibo; Marc Lanctot; Michael Johanson; Wojciech M. Czarnecki; Thore Graepel

    When autonomous agents interact in the same environment, they must often cooperate to achieve their goals. One way for agents to cooperate effectively is to form a team, make a binding agreement on a joint plan, and execute it. However, when agents are self-interested, the gains from team formation must be allocated appropriately to incentivize agreement. Various approaches for multi-agent negotiation

    更新日期:2020-08-05
  • Combining experts' causal judgments
    Artif. Intell. (IF 6.628) Pub Date : 2020-07-13
    Dalal Alrajeh; Hana Chockler; Joseph Y. Halpern

    Consider a policymaker who wants to decide which intervention to perform in order to change a currently undesirable situation. The policymaker has at her disposal a team of experts, each with their own understanding of the causal dependencies between different factors contributing to the outcome. The policymaker has varying degrees of confidence in the experts' opinions. She wants to combine their

    更新日期:2020-07-23
  • A technical survey on statistical modelling and design methods for crowdsourcing quality control
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-30
    Yuan Jin; Mark Carman; Ye Zhu; Yong Xiang

    Online crowdsourcing provides a scalable and inexpensive means to collect knowledge (e.g. labels) about various types of data items (e.g. text, audio, video). However, it is also known to result in large variance in the quality of recorded responses which often cannot be directly used for training machine learning systems. To resolve this issue, a lot of work has been conducted to control the response

    更新日期:2020-07-15
  • An approach for combining ethical principles with public opinion to guide public policy
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-16
    Edmond Awad; Michael Anderson; Susan Leigh Anderson; Beishui Liao

    We propose a framework for incorporating public opinion into policy making in situations where values are in conflict. This framework advocates creating vignettes representing value choices, eliciting the public's opinion on these choices, and using machine learning to extract principles that can serve as succinct statements of the policies implied by these choices and rules to guide the behavior of

    更新日期:2020-07-14
  • DEL-based epistemic planning: Decidability and complexity
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-22
    Thomas Bolander; Tristan Charrier; Sophie Pinchinat; François Schwarzentruber

    Epistemic planning can be used for decision making in multi-agent systems with distributed knowledge and capabilities. Dynamic Epistemic Logic (DEL) has been shown to provide a very natural and expressive framework for epistemic planning. In this paper, we present a systematic overview of known complexity and decidability results for epistemic planning based on DEL, as well as provide some new results

    更新日期:2020-07-10
  • Probabilistic reasoning about epistemic action narratives
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-29
    Fabio Aurelio D'Asaro; Antonis Bikakis; Luke Dickens; Rob Miller

    We propose the action language EPEC – Epistemic Probabilistic Event Calculus – that supports probabilistic, epistemic reasoning about narratives of action occurrences and environmentally triggered events, and in particular facilitates reasoning about future belief-conditioned actions and their consequences in domains that include both perfect and imperfect sensing actions. To provide a declarative

    更新日期:2020-07-03
  • Automated temporal equilibrium analysis: Verification and synthesis of multi-player games
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-26
    Julian Gutierrez; Muhammad Najib; Giuseppe Perelli; Michael Wooldridge

    In the context of multi-agent systems, the rational verification problem is concerned with checking which temporal logic properties will hold in a system when its constituent agents are assumed to behave rationally and strategically in pursuit of individual objectives. Typically, those objectives are expressed as temporal logic formulae which the relevant agent desires to see satisfied. Unfortunately

    更新日期:2020-07-03
  • Old techniques in new ways: Clause weighting, unit propagation and hybridization for maximum satisfiability
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-29
    Shaowei Cai; Zhendong Lei

    Maximum Satisfiability (MaxSAT) is a basic and important constraint optimization problem. When dealing with both hard and soft constraints, the MaxSAT problem is referred to as Partial MaxSAT, which has been used to effectively solve many combinatorial optimization problems in real world. The local search method and the SAT-based method are two popular methods for Partial MaxSAT. Nevertheless, local

    更新日期:2020-07-02
  • Evaluation of the moral permissibility of action plans
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-16
    Felix Lindner; Robert Mattmüller; Bernhard Nebel

    Research in classical planning so far has been mainly concerned with generating a satisficing or an optimal plan. However, if such systems are used to make decisions that are relevant to humans, one should also consider the ethical consequences generated plans can have. Traditionally, ethical principles are formulated in an action-based manner, allowing to judge the execution of one action. We show

    更新日期:2020-06-23
  • Designing normative theories for ethical and legal reasoning: LogiKEy framework, methodology, and tool support
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-12
    Christoph Benzmüller; Xavier Parent; Leendert van der Torre

    A framework and methodology—termed LogiKEy—for the design and engineering of ethical reasoners, normative theories and deontic logics is presented. The overall motivation is the development of suitable means for the control and governance of intelligent autonomous systems. LogiKEy's unifying formal framework is based on semantical embeddings of deontic logics, logic combinations and ethico-legal domain

    更新日期:2020-06-23
  • Memetic algorithms outperform evolutionary algorithms in multimodal optimisation
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-11
    Phan Trung Hai Nguyen; Dirk Sudholt

    Memetic algorithms integrate local search into an evolutionary algorithm to combine the advantages of rapid exploitation and global optimisation. We provide a rigorous runtime analysis of memetic algorithms on the Hurdle problem, a landscape class of tunable difficulty with a “big valley structure”, a characteristic feature of many hard combinatorial optimisation problems. A parameter called hurdle

    更新日期:2020-06-11
  • Boolean algebras of conditionals, probability and logic
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-10
    Tommaso Flaminio; Lluis Godo; Hykel Hosni

    This paper presents an investigation on the structure of conditional events and on the probability measures which arise naturally in that context. In particular we introduce a construction which defines a (finite) Boolean algebra of conditionals from any (finite) Boolean algebra of events. By doing so we distinguish the properties of conditional events which depend on probability and those which are

    更新日期:2020-06-10
  • Effective footstep planning using homotopy-class guidance
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-10
    Vinitha Ranganeni; Sahit Chintalapudi; Oren Salzman; Maxim Likhachev

    Planning the motion for humanoid robots is a computationally-complex task due to the high dimensionality of the system. Thus, a common approach is to first plan in the low-dimensional space induced by the robot's feet—a task referred to as footstep planning. This low-dimensional plan is then used to guide the full motion of the robot. One approach that has proven successful in footstep planning is

    更新日期:2020-06-10
  • Handling and measuring inconsistency in non-monotonic logics
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-10
    Markus Ulbricht; Matthias Thimm; Gerhard Brewka

    We address the issue of quantitatively assessing the severity of inconsistencies in non-monotonic frameworks. While measuring inconsistency in classical logics has been investigated for some time now, taking the non-monotonicity into account poses new challenges. In order to tackle them, we focus on the structure of minimal strongly K-inconsistent subsets of a knowledge base K—a sound generalization

    更新日期:2020-06-10
  • On the limits of forgetting in Answer Set Programming
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-10
    Ricardo Gonçalves; Matthias Knorr; João Leite; Stefan Woltran

    Selectively forgetting information while preserving what matters the most is becoming an increasingly important issue in many areas, including in knowledge representation and reasoning. Depending on the application at hand, forgetting operators are defined to obey different sets of desirable properties. It turns out that, of the myriad of desirable properties discussed in the context of forgetting

    更新日期:2020-06-10
  • Interpretable time series kernel analytics by pre-image estimation
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-10
    Thao Tran Thi Phuong; Ahlame Douzal-Chouakria; Saeed Varasteh Yazdi; Paul Honeine; Patrick Gallinari

    Kernel methods are known to be effective to analyse complex objects by implicitly embedding them into some feature space. To interpret and analyse the obtained results, it is often required to restore in the input space the results obtained in the feature space, by using pre-image estimation methods. This work proposes a new closed-form pre-image estimation method for time series kernel analytics that

    更新日期:2020-06-10
  • The distortion of distributed voting
    Artif. Intell. (IF 6.628) Pub Date : 2020-06-09
    Aris Filos-Ratsikas; Evi Micha; Alexandros A. Voudouris

    Voting can abstractly model any decision-making scenario and as such it has been extensively studied over the decades. Recently, the related literature has focused on quantifying the impact of utilizing only limited information in the voting process on the societal welfare for the outcome, by bounding the distortion of voting rules. Even though there has been significant progress towards this goal

    更新日期:2020-06-09
  • Dynamic term-modal logics for first-order epistemic planning
    Artif. Intell. (IF 6.628) Pub Date : 2020-05-27
    Andrés Occhipinti Liberman; Andreas Achen; Rasmus Kræmmer Rendsvig

    Many classical planning frameworks are built on first-order languages. The first-order expressive power is desirable for compactly representing actions via schemas, and for specifying quantified conditions such as ¬∃xblocks_door(x). In contrast, several recent epistemic planning frameworks are built on propositional epistemic logic. The epistemic language is useful to describe planning problems involving

    更新日期:2020-05-27
  • On the equivalence of optimal recommendation sets and myopically optimal query sets
    Artif. Intell. (IF 6.628) Pub Date : 2020-05-26
    Paolo Viappiani; Craig Boutilier

    Preference elicitation is an important component in many AI applications, including decision support and recommender systems. Such systems must assess user preferences, based on interactions with their users, and make recommendations using (possibly incomplete and imprecise) beliefs about those preferences. Mechanisms for explicit preference elicitation—asking users to answer direct queries about their

    更新日期:2020-05-26
  • The logic of gossiping
    Artif. Intell. (IF 6.628) Pub Date : 2020-05-26
    Hans van Ditmarsch; Wiebe van der Hoek; Louwe B. Kuijer

    The so-called gossip problem is a formal model of peer-to-peer communication. In order to perform such communication efficiently, it is important to keep track of what agents know about who holds what information at a given point in time. The knowledge that the agents possess depends strongly on the particular type of communication that is used. Here, we formally define a large number of different

    更新日期:2020-05-26
  • PopMNet: Generating structured pop music melodies using neural networks
    Artif. Intell. (IF 6.628) Pub Date : 2020-05-26
    Jian Wu; Xiaoguang Liu; Xiaolin Hu; Jun Zhu

    Recently, many deep learning models have been proposed to generate symbolic melodies. However, generating pop music melodies with well organized structures remains to be challenging. In this paper, we present a melody structure-based model called PopMNet to generate structured pop music melodies. The melody structure is defined by pairwise relations, specifically, repetition and sequence, between all

    更新日期:2020-05-26
  • Verification of multi-agent systems with public actions against strategy logic
    Artif. Intell. (IF 6.628) Pub Date : 2020-05-15
    Francesco Belardinelli; Alessio Lomuscio; Aniello Murano; Sasha Rubin

    Model checking multi-agent systems, in which agents are distributed and thus may have different observations of the world, against strategic behaviours is known to be a complex problem in a number of settings. There are traditionally two ways of ameliorating this complexity: imposing a hierarchy on the observations of the agents, or restricting agent actions so that they are observable by all agents

    更新日期:2020-05-15
  • Special issue on autonomous agents modelling other agents: Guest editorial
    Artif. Intell. (IF 6.628) Pub Date : 2020-05-13
    Stefano V. Albrecht; Peter Stone; Michael P. Wellman

    Much research in artificial intelligence is concerned with enabling autonomous agents to reason about various aspects of other agents (such as their beliefs, goals, plans, or decisions) and to utilise such reasoning for effective interaction. This special issue contains new technical contributions addressing open problems in autonomous agents modelling other agents, as well as research perspectives

    更新日期:2020-05-13
  • Compact and efficient encodings for planning in factored state and action spaces with learned Binarized Neural Network transition models
    Artif. Intell. (IF 6.628) Pub Date : 2020-05-12
    Buser Say; Scott Sanner

    In this paper, we leverage the efficiency of Binarized Neural Networks (BNNs) to learn complex state transition models of planning domains with discretized factored state and action spaces. In order to directly exploit this transition structure for planning, we present two novel compilations of the learned factored planning problem with BNNs based on reductions to Weighted Partial Maximum Boolean Satisfiability

    更新日期:2020-05-12
  • Complexity of abstract argumentation under a claim-centric view
    Artif. Intell. (IF 6.628) Pub Date : 2020-05-12
    Wolfgang Dvořák; Stefan Woltran

    Abstract argumentation frameworks have been introduced by Dung as part of an argumentation process, where arguments and conflicts are derived from a given knowledge base. It is solely this relation between arguments that is then used in order to identify acceptable sets of arguments. A final step concerns the acceptance status of particular statements by reviewing the actual contents of the acceptable

    更新日期:2020-05-12
  • On strengthening the logic of iterated belief revision: Proper ordinal interval operators
    Artif. Intell. (IF 6.628) Pub Date : 2020-05-07
    Richard Booth; Jake Chandler

    Darwiche and Pearl's seminal 1997 article outlined a number of baseline principles for a logic of iterated belief revision. These principles, the DP postulates, have been supplemented in a number of alternative ways. However, most of the suggestions for doing so have been radical enough to result in a dubious ‘reductionist’ principle that identifies belief states with orderings of worlds. The present

    更新日期:2020-05-07
  • On the complexity of reasoning about opinion diffusion under majority dynamics
    Artif. Intell. (IF 6.628) Pub Date : 2020-04-27
    Vincenzo Auletta; Diodato Ferraioli; Gianluigi Greco

    We study opinion diffusion on social graphs where agents hold binary opinions and where social pressure leads them to conform to the opinion manifested by the majority of their neighbors. We provide bounds relating the number of agents that suffice to spread an opinion to all other agents with the number of required propagation steps. Bounds are established constructively, via polynomial time algorithms

    更新日期:2020-04-27
  • Knowing the price of success
    Artif. Intell. (IF 6.628) Pub Date : 2020-04-24
    Rui Cao; Pavel Naumov

    If an agent, or a coalition of agents, knows that it has a strategy to achieve a certain outcome, it does not mean that the agent knows what the strategy is. Even if the agent knows what the strategy is, she might not know the price of executing this strategy. The article considers modality “the coalition not only knows the strategy, but also knows an upper bound on the price of executing the strategy”

    更新日期:2020-04-24
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