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  • Combining gaze and AI planning for online human intention recognition
    Artif. Intell. (IF 4.483) Pub Date : 2020-04-01
    Ronal Singh; Tim Miller; Joshua Newn; Eduardo Velloso; Frank Vetere; Liz Sonenberg

    Intention recognition is the process of using behavioural cues, such as deliberative actions, eye gaze, and gestures, to infer an agent's goals or future behaviour. In artificial intelligence, one approach for intention recognition is to use a model of possible behaviour to rate intentions as more likely if they are a better ‘fit’ to actions observed so far. In this paper, we draw from literature linking

    更新日期:2020-04-01
  • Compatibility, desirability, and the running intersection property
    Artif. Intell. (IF 4.483) Pub Date : 2020-03-30
    Enrique Miranda; Marco Zaffalon

    Compatibility is the problem of checking whether some given probabilistic assessments have a common joint probabilistic model. When the assessments are unconditional, the problem is well established in the literature and finds a solution through the running intersection property (RIP). This is not the case of conditional assessments. In this paper, we study the compatibility problem in a very general

    更新日期:2020-03-30
  • CPCES: A Planning Framework to Solve Conformant Planning Problems through a Counterexample Guided Refinement
    Artif. Intell. (IF 4.483) Pub Date : 2020-03-26
    Alban Grastien; Enrico Scala

    We introduce cpces, a novel planner for the problem of deterministic conformant planning. cpces solves the problem by producing candidate plans based on a sample of the initial belief state, searching for counter-examples to these plans, and assigning these counter-examples to the sample, until a valid plan has been produced or the problem has been proved unfeasible. On top of providing a means to

    更新日期:2020-03-27
  • An epistemic logic of blameworthiness
    Artif. Intell. (IF 4.483) Pub Date : 2020-03-26
    Pavel Naumov; Jia Tao

    Blameworthiness of an agent or a coalition of agents can be defined in terms of the principle of alternative possibilities: for the coalition to be responsible for an outcome, the outcome must take place and the coalition should be a minimal one that had a strategy to prevent the outcome. In this article we argue that in the settings with imperfect information, not only should the coalition have had

    更新日期:2020-03-27
  • Intention as commitment toward time
    Artif. Intell. (IF 4.483) Pub Date : 2020-03-26
    Marc van Zee; Dragan Doder; Leendert van der Torre; Mehdi Dastani; Thomas Icard; Eric Pacuit

    In this paper we address the interplay among intention, time, and belief in dynamic environments. The first contribution is a logic for reasoning about intention, time and belief, in which assumptions of intentions are represented by preconditions of intended actions. Intentions and beliefs are coherent as long as these assumptions are not violated, i.e. as long as intended actions can be performed

    更新日期:2020-03-27
  • On pruning search trees of impartial games
    Artif. Intell. (IF 4.483) Pub Date : 2020-03-24
    Piotr Beling; Marek Rogalski

    In this paper we study computing Sprague-Grundy values for short impartial games under the normal play convention. We put forward new game-agnostic methods for effective pruning search trees of impartial games. These algorithms are inspired by the α-β, a well-known pruning method for minimax trees. However, our algorithms prune trees whose node values are assigned by the mex function instead of min/max

    更新日期:2020-03-24
  • Adapting a kidney exchange algorithm to align with human values
    Artif. Intell. (IF 4.483) Pub Date : 2020-03-24
    Rachel Freedman; Jana Schaich Borg; Walter Sinnott-Armstrong; John P. Dickerson; Vincent Conitzer

    The efficient and fair allocation of limited resources is a classical problem in economics and computer science. In kidney exchanges, a central market maker allocates living kidney donors to patients in need of an organ. Patients and donors in kidney exchanges are prioritized using ad-hoc weights decided on by committee and then fed into an allocation algorithm that determines who gets what—and who

    更新日期:2020-03-24
  • Qualitative Case-Based Reasoning and Learning
    Artif. Intell. (IF 4.483) Pub Date : 2020-03-20
    Thiago Pedro Donadon Homem; Paulo Eduardo Santos; Anna Helena Reali Costa; Reinaldo Augusto da Costa Bianchi; Ramon Lopez de Mantaras

    The development of autonomous agents that perform tasks with the same dexterity as performed by humans is one of the challenges of artificial intelligence and robotics. This motivates the research on intelligent agents, since the agent must choose the best action in a dynamic environment in order to maximise the final score. In this context, the present paper introduces a novel algorithm for Qualitative

    更新日期:2020-03-21
  • Limited Lookahead in Imperfect-Information Games
    Artif. Intell. (IF 4.483) Pub Date : 2020-03-19
    Christian Kroer; Tuomas Sandholm

    Limited lookahead has been studied for decades in perfect-information games. We initiate a new direction via two simultaneous deviation points: generalization to imperfect-information games and a game-theoretic approach. We study how one should act when facing an opponent whose lookahead is limited. We study this for opponents that differ based on their lookahead depth, based on whether they, too,

    更新日期:2020-03-20
  • Fair navigation planning: a resource for characterizing and designing fairness in mobile robots
    Artif. Intell. (IF 4.483) Pub Date : 2020-03-18
    Martim Brandão; Marina Jirtoka; Helena Webb; Paul Luff

    In recent years, the development and deployment of autonomous systems such as mobile robots have been increasingly common. Investigating and implementing ethical considerations such as fairness in autonomous systems is an important problem that is receiving increased attention, both because of recent findings of their potential undesired impacts and a related surge in ethical principles and guidelines

    更新日期:2020-03-19
  • Batch repair actions for automated troubleshooting
    Artif. Intell. (IF 4.483) Pub Date : 2020-03-16
    Hilla Shinitzky; Roni Stern

    Repairing a set of components as a batch is often cheaper than repairing each of them separately. A primary reason for this is that initiating a repair action and testing the system after performing a repair action often incurs non-negligible overhead. However, most troubleshooting algorithms proposed to date do not consider the option of performing batch repair actions. In this work we close this

    更新日期:2020-03-16
  • Automated construction of bounded-loss imperfect-recall abstractions in extensive-form games
    Artif. Intell. (IF 4.483) Pub Date : 2020-02-14
    Jiří Čermák; Viliam Lisý; Branislav Bošanský

    Extensive-form games (EFGs) model finite sequential interactions between players. The amount of memory required to represent these games is the main bottleneck of algorithms for computing optimal strategies and the size of these strategies is often impractical for real-world applications. A common approach to tackle the memory bottleneck is to use information abstraction that removes parts of information

    更新日期:2020-02-20
  • How do fairness definitions fare? Testing public attitudes towards three algorithmic definitions of fairness in loan allocations
    Artif. Intell. (IF 4.483) Pub Date : 2020-02-20
    Nripsuta Ani Saxena; Karen Huang; Evan DeFilippis; Goran Radanovic; David C. Parkes; Yang Liu

    What is the best way to define algorithmic fairness? While many definitions of fairness have been proposed in the computer science literature, there is no clear agreement over a particular definition. In this work, we investigate ordinary people's perceptions of three of these fairness definitions. Across three online experiments, we test which definitions people perceive to be the fairest in the context

    更新日期:2020-02-20
  • Autoepistemic equilibrium logic and epistemic specifications
    Artif. Intell. (IF 4.483) Pub Date : 2020-02-19
    Luis Fariñas del Cerro; Andreas Herzig; Ezgi Iraz Su

    Epistemic specifications extend disjunctive answer-set programs by an epistemic modal operator that may occur in the body of rules. Their semantics is in terms of world views, which are sets of answer sets, and the idea is that the epistemic modal operator quantifies over these answer sets. Several such semantics were proposed in the literature. We here propose a new semantics that is based on the

    更新日期:2020-02-20
  • Robust Learning with Imperfect Privileged Information
    Artif. Intell. (IF 4.483) Pub Date : 2020-02-12
    Xue Li; Bo Du; Chang Xu; Yipeng Zhang; Lefei Zhang; Dacheng Tao

    In the learning using privileged information (LUPI) paradigm, example data cannot always be clean, while the gathered privileged information can be imperfect in practice. Here, imperfect privileged information can refer to auxiliary information that is not always accurate or perturbed by noise, or alternatively to incomplete privileged information, where privileged information is only available for

    更新日期:2020-02-12
  • Rethinking epistemic logic with belief bases
    Artif. Intell. (IF 4.483) Pub Date : 2020-02-10
    Emiliano Lorini

    We introduce a new semantics for a family of logics of explicit and implicit belief based on the concept of multi-agent belief base. Differently from standard semantics for epistemic logic in which the notions of possible world and doxastic/epistemic alternative are primitive, in our semantics they are non-primitive but are computed from the concept of belief base. We provide complete axiomatizations

    更新日期:2020-02-10
  • Regression and Progression in Stochastic Domains
    Artif. Intell. (IF 4.483) Pub Date : 2020-01-30
    Vaishak Belle; Hector J. Levesque

    Reasoning about degrees of belief in uncertain dynamic worlds is fundamental to many applications, such as robotics and planning, where actions modify state properties and sensors provide measurements, both of which are prone to noise. With the exception of limited cases such as Gaussian processes over linear phenomena, belief state evolution can be complex and hard to reason with in a general way

    更新日期:2020-01-31
  • Swarm Intelligence for Self-Organized Clustering
    Artif. Intell. (IF 4.483) Pub Date : 2020-01-28
    Michael C. Thrun; Alfred Ultsch

    Algorithms implementing populations of agents which interact with one another and sense their environment may exhibit emergent behavior such as self-organization and swarm intelligence. Here a swarm system, called Databionic swarm (DBS), is introduced which is able to adapt itself to structures of high-dimensional data characterized by distance and/or density-based structures in the data space. By

    更新日期:2020-01-29
  • Ethical approaches and autonomous systems
    Artif. Intell. (IF 4.483) Pub Date : 2020-01-21
    T.J.M. Bench-Capon

    In this paper we consider how the three main approaches to ethics – deontology, consequentialism and virtue ethics – relate to the implementation of ethical agents. We provide a description of each approach and how agents might be implemented by designers following the different approaches. Although there are numerous examples of agents implemented within the consequentialist and deontological approaches

    更新日期:2020-01-22
  • Epistemic graphs for representing and reasoning with positive and negative influences of arguments
    Artif. Intell. (IF 4.483) Pub Date : 2020-01-13
    Anthony Hunter; Sylwia Polberg; Matthias Thimm

    This paper introduces epistemic graphs as a generalization of the epistemic approach to probabilistic argumentation. In these graphs, an argument can be believed or disbelieved up to a given degree, thus providing a more fine–grained alternative to the standard Dung's approaches when it comes to determining the status of a given argument. Furthermore, the flexibility of the epistemic approach allows

    更新日期:2020-01-13
  • Story embedding: Learning distributed representations of stories based on character networks
    Artif. Intell. (IF 4.483) Pub Date : 2020-01-13
    O-Joun Lee; Jason J. Jung

    This study aims to learn representations of stories in narrative works (i.e., creative works that contain stories) using fixed-length vectors. Vector representations of stories enable us to compare narrative works regardless of their media or formats. To computationally represent stories, we focus on social networks among characters (character networks). We assume that the structural features of the

    更新日期:2020-01-13
  • Synchronous bidirectional inference for neural sequence generation
    Artif. Intell. (IF 4.483) Pub Date : 2020-01-08
    Jiajun Zhang; Long Zhou; Yang Zhao; Chengqing Zong

    In sequence to sequence generation tasks (e.g. machine translation and abstractive summarization), inference is generally performed in a left-to-right manner to produce the result token by token. The neural approaches, such as LSTM and self-attention networks, are now able to make full use of all the predicted history hypotheses from left side during inference, but cannot meanwhile access any future

    更新日期:2020-01-09
  • Definability for model counting
    Artif. Intell. (IF 4.483) Pub Date : 2020-01-07
    Jean-Marie Lagniez; Emmanuel Lonca; Pierre Marquis

    We define and evaluate a new preprocessing technique for propositional model counting. This technique leverages definability, i.e., the ability to determine that some gates are implied by the input formula Σ. Such gates can be exploited to simplify Σ without modifying its number of models. Unlike previous techniques based on gate detection and replacement, gates do not need to be made explicit in our

    更新日期:2020-01-07
  • Relative inconsistency measures
    Artif. Intell. (IF 4.483) Pub Date : 2020-01-07
    Philippe Besnard; John Grant

    The literature on inconsistency measures has ignored a distinction, that is, differentiating absolute measures and relative measures. An absolute measure gives the total amount of inconsistency in the knowledge base but a relative measure computes, by some criteria, the proportion of the base that is inconsistent. To compare the inconsistency measures, researchers have proposed postulates for such

    更新日期:2020-01-07
  • The Hanabi challenge: A new frontier for AI research
    Artif. Intell. (IF 4.483) Pub Date : 2019-11-27
    Nolan Bard; Jakob N. Foerster; Sarath Chandar; Neil Burch; Marc Lanctot; H. Francis Song; Emilio Parisotto; Vincent Dumoulin; Subhodeep Moitra; Edward Hughes; Iain Dunning; Shibl Mourad; Hugo Larochelle; Marc G. Bellemare; Michael Bowling

    From the early days of computing, games have been important testbeds for studying how well machines can do sophisticated decision making. In recent years, machine learning has made dramatic advances with artificial agents reaching superhuman performance in challenge domains like Go, Atari, and some variants of poker. As with their predecessors of chess, checkers, and backgammon, these game domains

    更新日期:2020-01-04
  • When autonomous agents model other agents: An appeal for altered judgment coupled with mouths, ears, and a little more tape
    Artif. Intell. (IF 4.483) Pub Date : 2019-12-16
    Jacob W. Crandall

    Agent modeling has rightfully garnered much attention in the design and study of autonomous agents that interact with other agents. However, despite substantial progress to date, existing agent-modeling methods too often (a) have unrealistic computational requirements and data needs; (b) fail to properly generalize across environments, tasks, and associates; and (c) guide behavior toward inefficient

    更新日期:2020-01-04
  • Polynomial rewritings from expressive Description Logics with closed predicates to variants of Datalog
    Artif. Intell. (IF 4.483) Pub Date : 2019-12-16
    Shqiponja Ahmetaj; Magdalena Ortiz; Mantas Šimkus

    In many scenarios, complete and incomplete information coexist. For this reason, the knowledge representation and database communities have long shown interest in simultaneously supporting the closed- and the open-world views when reasoning about logic theories. Here we consider the setting of querying possibly incomplete data using logic theories, formalized as the evaluation of an ontology-mediated

    更新日期:2020-01-04
  • The computational complexity of angry birds
    Artif. Intell. (IF 4.483) Pub Date : 2020-01-03
    Matthew Stephenson; Jochen Renz; Xiaoyu Ge

    The physics-based simulation game Angry Birds has been heavily researched by the AI community over the past five years, and has been the subject of a popular AI competition that is currently held annually as part of a leading AI conference. Developing intelligent agents that can play this game effectively has been an incredibly complex and challenging problem for traditional AI techniques to solve

    更新日期:2020-01-04
  • SCCWalk: An efficient local search algorithm and its improvements for maximum weight clique problem
    Artif. Intell. (IF 4.483) Pub Date : 2020-01-02
    Yiyuan Wang; Shaowei Cai; Jiejiang Chen; Minghao Yin

    The maximum weight clique problem (MWCP) is an important generalization of the maximum clique problem with wide applications. In this study, we develop two efficient local search algorithms for MWCP, namely SCCWalk and SCCWalk4L, where SCCWalk4L is improved from SCCWalk for large graphs. There are two main ideas in SCCWalk, including strong configuration checking (SCC) and walk perturbation. SCC is

    更新日期:2020-01-04
  • Reasoning about uncertain parameters and agent behaviors through encoded experiences and belief planning
    Artif. Intell. (IF 4.483) Pub Date : 2019-12-27
    Akinobu Hayashi; Dirk Ruiken; Tadaaki Hasegawa; Christian Goerick

    Robots are expected to handle increasingly complex tasks. Such tasks often include interaction with objects or collaboration with other agents. One of the key challenges for reasoning in such situations is the lack of accurate models that hinders the effectiveness of planners. We present a system for online model adaptation that continuously validates and improves models while solving tasks with a

    更新日期:2020-01-04
  • Learning in the Machine: Random Backpropagation and the Deep Learning Channel.
    Artif. Intell. (IF 4.483) Pub Date : 2018-05-08
    Pierre Baldi,Peter Sadowski,Zhiqin Lu

    Random backpropagation (RBP) is a variant of the backpropagation algorithm for training neural networks, where the transpose of the forward matrices are replaced by fixed random matrices in the calculation of the weight updates. It is remarkable both because of its effectiveness, in spite of using random matrices to communicate error information, and because it completely removes the taxing requirement

    更新日期:2019-11-01
  • Methods for solving reasoning problems in abstract argumentation - A survey.
    Artif. Intell. (IF 4.483) Pub Date : 2015-03-05
    Günther Charwat,Wolfgang Dvořák,Sarah A Gaggl,Johannes P Wallner,Stefan Woltran

    Within the last decade, abstract argumentation has emerged as a central field in Artificial Intelligence. Besides providing a core formalism for many advanced argumentation systems, abstract argumentation has also served to capture several non-monotonic logics and other AI related principles. Although the idea of abstract argumentation is appealingly simple, several reasoning problems in this formalism

    更新日期:2019-11-01
  • Modeling the Complex Dynamics and Changing Correlations of Epileptic Events.
    Artif. Intell. (IF 4.483) Pub Date : 2014-10-07
    Drausin F Wulsin,Emily B Fox,Brian Litt

    Patients with epilepsy can manifest short, sub-clinical epileptic "bursts" in addition to full-blown clinical seizures. We believe the relationship between these two classes of events-something not previously studied quantitatively-could yield important insights into the nature and intrinsic dynamics of seizures. A goal of our work is to parse these complex epileptic events into distinct dynamic regimes

    更新日期:2019-11-01
  • The Dropout Learning Algorithm.
    Artif. Intell. (IF 4.483) Pub Date : 2014-04-29
    Pierre Baldi,Peter Sadowski

    Dropout is a recently introduced algorithm for training neural network by randomly dropping units during training to prevent their co-adaptation. A mathematical analysis of some of the static and dynamic properties of dropout is provided using Bernoulli gating variables, general enough to accommodate dropout on units or connections, and with variable rates. The framework allows a complete analysis

    更新日期:2019-11-01
  • Using Wikipedia to learn semantic feature representations of concrete concepts in neuroimaging experiments.
    Artif. Intell. (IF 4.483) Pub Date : 2012-12-18
    Francisco Pereira,Matthew Botvinick,Greg Detre

    In this paper we show that a corpus of a few thousand Wikipedia articles about concrete or visualizable concepts can be used to produce a low-dimensional semantic feature representation of those concepts. The purpose of such a representation is to serve as a model of the mental context of a subject during functional magnetic resonance imaging (fMRI) experiments. A recent study [19] showed that it was

    更新日期:2019-11-01
  • The Local Geometry of Multiattribute Tradeoff Preferences.
    Artif. Intell. (IF 4.483) Pub Date : 2011-04-30
    Michael McGeachie,Jon Doyle

    Existing representations for multiattribute ceteris paribus preference statements have provided useful treatments and clear semantics for qualitative comparisons, but have not provided similarly clear representations or semantics for comparisons involving quantitative tradeoffs. We use directional derivatives and other concepts from elementary differential geometry to interpret conditional multiattribute

    更新日期:2019-11-01
  • Updating action domain descriptions.
    Artif. Intell. (IF 4.483) Pub Date : 2010-12-15
    Thomas Eiter,Esra Erdem,Michael Fink,Ján Senko

    Incorporating new information into a knowledge base is an important problem which has been widely investigated. In this paper, we study this problem in a formal framework for reasoning about actions and change. In this framework, action domains are described in an action language whose semantics is based on the notion of causality. Unlike the formalisms considered in the related work, this language

    更新日期:2019-11-01
  • A comparative runtime analysis of heuristic algorithms for satisfiability problems.
    Artif. Intell. (IF 4.483) Pub Date : 2010-02-04
    Yuren Zhou,Jun He,Qing Nie

    The satisfiability problem is a basic core NP-complete problem. In recent years, a lot of heuristic algorithms have been developed to solve this problem, and many experiments have evaluated and compared the performance of different heuristic algorithms. However, rigorous theoretical analysis and comparison are rare. This paper analyzes and compares the expected runtime of three basic heuristic algorithms:

    更新日期:2019-11-01
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