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  • 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
  • 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:2020-07-13
  • 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
  • CPCES: A planning framework to solve conformant planning problems through a counterexample guided refinement
    Artif. Intell. (IF 6.628) 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:2020-04-20
  • Combining gaze and AI planning for online human intention recognition
    Artif. Intell. (IF 6.628) 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:2020-04-20
  • On quasi-inconsistency and its complexity
    Artif. Intell. (IF 6.628) Pub Date : 2020-04-15
    Carl Corea; Matthias Thimm

    We address the issue of analyzing potential inconsistencies in knowledge bases. This refers to knowledge bases that contain rules which will always be activated together, and the knowledge base will become inconsistent, should these rules be activated. We investigate this problem in the context of the industrial use-case of business rule management, where it is often required that sets of (only) rules

    更新日期:2020-04-20
  • Swarm Intelligence for Self-Organized Clustering
    Artif. Intell. (IF 6.628) 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:2020-04-20
  • Compatibility, desirability, and the running intersection property
    Artif. Intell. (IF 6.628) 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
  • An epistemic logic of blameworthiness
    Artif. Intell. (IF 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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
  • Ethical approaches and autonomous systems
    Artif. Intell. (IF 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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 6.628) 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
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