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37,508 | Multi-Agent Q-Learning for Minimizing Demand-Supply Power Deficit in
Microgrids | cs.SY | We consider the problem of minimizing the difference in the demand and the
supply of power using microgrids. We setup multiple microgrids, that provide
electricity to a village. They have access to the batteries that can store
renewable power and also the electrical lines from the main grid. During each
time period, th... | computer science |
37,509 | Non-FPT lower bounds for structural restrictions of decision DNNF | cs.AI | We give a non-FPT lower bound on the size of structured decision DNNF and
OBDD with decomposable AND-nodes representing CNF-formulas of bounded incidence
treewidth. Both models are known to be of FPT size for CNFs of bounded primal
treewidth. To the best of our knowledge this is the first parameterized
separation of pr... | computer science |
37,510 | Navigation Objects Extraction for Better Content Structure Understanding | cs.AI | Existing works for extracting navigation objects from webpages focus on
navigation menus, so as to reveal the information architecture of the site.
However, web 2.0 sites such as social networks, e-commerce portals etc. are
making the understanding of the content structure in a web site increasingly
difficult. Dynamic ... | computer science |
37,511 | Novel Sensor Scheduling Scheme for Intruder Tracking in Energy Efficient
Sensor Networks | cs.AI | We consider the problem of tracking an intruder using a network of wireless
sensors. For tracking the intruder at each instant, the optimal number and the
right configuration of sensors has to be powered. As powering the sensors
consumes energy, there is a trade off between accurately tracking the position
of the intru... | computer science |
37,512 | Learning to Price with Reference Effects | cs.GT | As a firm varies the price of a product, consumers exhibit reference effects,
making purchase decisions based not only on the prevailing price but also the
product's price history. We consider the problem of learning such behavioral
patterns as a monopolist releases, markets, and prices products. This context
calls for... | computer science |
37,513 | Behavior Trees in Robotics and AI: An Introduction | cs.RO | A Behavior Tree (BT) is a way to structure the switching between different
tasks in an autonomous agent, such as a robot or a virtual entity in a computer
game. BTs are a very efficient way of creating complex systems that are both
modular and reactive. These properties are crucial in many applications, which
has led t... | computer science |
37,514 | Inferring Networked Device Categories from Low-Level Activity Indicators | cs.NI | We study the problem of inferring the type of a networked device in a home
network by leveraging low level traffic activity indicators seen at commodity
home gateways. We analyze a dataset of detailed device network activity
obtained from 240 subscriber homes of a large European ISP and extract a number
of traffic and ... | computer science |
37,515 | Convergence, Continuity and Recurrence in Dynamic Epistemic Logic | cs.LO | The paper analyzes dynamic epistemic logic from a topological perspective.
The main contribution consists of a framework in which dynamic epistemic logic
satisfies the requirements for being a topological dynamical system thus
interfacing discrete dynamic logics with continuous mappings of dynamical
systems. The settin... | computer science |
37,516 | An Improved Algorithm for E-Generalization | cs.LO | E-generalization computes common generalizations of given ground terms w.r.t.
a given equational background theory E. In 2005 [arXiv:1403.8118], we had
presented a computation approach based on standard regular tree grammar
algorithms, and a Prolog prototype implementation. In this report, we present
algorithmic improv... | computer science |
37,517 | Automation of Android Applications Testing Using Machine Learning
Activities Classification | cs.SE | Mobile applications are being used every day by more than half of the world's
population to perform a great variety of tasks. With the increasingly
widespread usage of these applications, the need arises for efficient
techniques to test them. Many frameworks allow automating the process of
application testing, however ... | computer science |
37,518 | Maintaining Ad-Hoc Communication Network in Area Protection Scenarios
with Adversarial Agents | cs.MA | We address a problem of area protection in graph-based scenarios with
multiple mobile agents where connectivity is maintained among agents to ensure
they can communicate. The problem consists of two adversarial teams of agents
that move in an undirected graph shared by both teams. Agents are placed in
vertices of the g... | computer science |
37,519 | Exact Inference for Relational Graphical Models with Interpreted
Functions: Lifted Probabilistic Inference Modulo Theories | cs.AI | Probabilistic Inference Modulo Theories (PIMT) is a recent framework that
expands exact inference on graphical models to use richer languages that
include arithmetic, equalities, and inequalities on both integers and real
numbers. In this paper, we expand PIMT to a lifted version that also processes
random functions an... | computer science |
37,520 | Speeding-up the decision making of a learning agent using an ion trap
quantum processor | cs.AI | We report a proof-of-principle experimental demonstration of the quantum
speed-up for learning agents utilizing a small-scale quantum information
processor based on radiofrequency-driven trapped ions. The decision-making
process of a quantum learning agent within the projective simulation paradigm
for machine learning ... | computer science |
37,521 | Artificial Intelligence and Data Science in the Automotive Industry | cs.AI | Data science and machine learning are the key technologies when it comes to
the processes and products with automatic learning and optimization to be used
in the automotive industry of the future. This article defines the terms "data
science" (also referred to as "data analytics") and "machine learning" and how
they ar... | computer science |
37,522 | Proceedings First Workshop on Formal Verification of Autonomous Vehicles | cs.SY | These are the proceedings of the workshop on Formal Verification of
Autonomous Vehicles, held on September 19th, 2017 in Turin, Italy, as an
affiliated workshop of the International Conference on integrated Formal
Methods (iFM 2017). The workshop aim is to bring together researchers from the
formal verification communi... | computer science |
37,523 | Rationally Biased Learning | cs.AI | Are human perception and decision biases grounded in a form of rationality?
You return to your camp after hunting or gathering. You see the grass moving.
You do not know the probability that a snake is in the grass. Should you cross
the grass - at the risk of being bitten by a snake - or make a long, hence
costly, deto... | computer science |
37,524 | Intelligent Subset Selection of Power Generators for Economic Dispatch | cs.CE | Sustainable and economical generation of electrical power is an essential and
mandatory component of infrastructure in today's world. Optimal generation
(generator subset selection) of power requires a careful evaluation of various
factors like type of source, generation, transmission & storage capacities,
congestion a... | computer science |
37,525 | The Shape of a Benedictine Monastery: The SaintGall Ontology | cs.AI | We present an OWL 2 ontology representing the Saint Gall plan, one of the
most ancient documents arrived intact to us, which describes the ideal model of
a Benedictine monastic complex that inspired the design of many European
monasteries. | computer science |
37,526 | Uncertainty measurement with belief entropy on interference effect in
Quantum-Like Bayesian Networks | cs.AI | Social dilemmas have been regarded as the essence of evolution game theory,
in which the prisoner's dilemma game is the most famous metaphor for the
problem of cooperation. Recent findings revealed people's behavior violated the
Sure Thing Principle in such games. Classic probability methodologies have
difficulty expla... | computer science |
37,527 | Prosocial learning agents solve generalized Stag Hunts better than
selfish ones | cs.AI | Deep reinforcement learning has become an important paradigm for constructing
agents that can enter complex multi-agent situations and improve their policies
through experience. One commonly used technique is reactive training - applying
standard RL methods while treating other agents as a part of the learner's
environ... | computer science |
37,528 | Mining relevant interval rules | cs.AI | This article extends the method of Garriga et al. for mining relevant rules
to numerical attributes by extracting interval-based pattern rules. We propose
an algorithm that extracts such rules from numerical datasets using the
interval-pattern approach from Kaytoue et al. This algorithm has been
implemented and evaluat... | computer science |
37,529 | Expert Opinion Extraction from a Biomedical Database | cs.AI | In this paper, we tackle the problem of extracting frequent opinions from
uncertain databases. We introduce the foundation of an opinion mining approach
with the definition of pattern and support measure. The support measure is
derived from the commitment definition. A new algorithm called OpMiner that
extracts the set... | computer science |
37,530 | Cellular Automaton Based Simulation of Large Pedestrian Facilities - A
Case Study on the Staten Island Ferry Terminals | cs.MA | Current metropolises largely depend on a functioning transport infrastructure
and the increasing demand can only be satisfied by a well organized mass
transit. One example for a crucial mass transit system is New York City's
Staten Island Ferry, connecting the two boroughs of Staten Island and Manhattan
with a regular ... | computer science |
37,531 | Discriminant chronicles mining: Application to care pathways analytics | cs.AI | Pharmaco-epidemiology (PE) is the study of uses and effects of drugs in well
defined populations. As medico-administrative databases cover a large part of
the population, they have become very interesting to carry PE studies. Such
databases provide longitudinal care pathways in real condition containing
timestamped car... | computer science |
37,532 | Autonomous Quadrotor Landing using Deep Reinforcement Learning | cs.AI | Landing an unmanned aerial vehicle (UAV) on a ground marker is an open
problem despite the effort of the research community. Previous attempts mostly
focused on the analysis of hand-crafted geometric features and the use of
external sensors in order to allow the vehicle to approach the land-pad. In
this article, we pro... | computer science |
37,533 | A Planning Approach to Monitoring Behavior of Computer Programs | cs.AI | We describe a novel approach to monitoring high level behaviors using
concepts from AI planning. Our goal is to understand what a program is doing
based on its system call trace. This ability is particularly important for
detecting malware. We approach this problem by building an abstract model of
the operating system ... | computer science |
37,534 | Aggregating incoherent agents who disagree | stat.OT | In this paper, we explore how we should aggregate the degrees of belief of of
a group of agents to give a single coherent set of degrees of belief, when at
least some of those agents might be probabilistically incoherent. There are a
number of way of aggregating degrees of belief, and there are a number of ways
of fixi... | computer science |
37,535 | Computing the Shapley Value in Allocation Problems: Approximations and
Bounds, with an Application to the Italian VQR Research Assessment Program | cs.GT | In allocation problems, a given set of goods are assigned to agents in such a
way that the social welfare is maximised, that is, the largest possible global
worth is achieved. When goods are indivisible, it is possible to use money
compensation to perform a fair allocation taking into account the actual
contribution of... | computer science |
37,536 | Learning with Opponent-Learning Awareness | cs.AI | Multi-agent settings are quickly gathering importance in machine learning.
Beyond a plethora of recent work on deep multi-agent reinforcement learning,
hierarchical reinforcement learning, generative adversarial networks and
decentralized optimization can all be seen as instances of this setting.
However, the presence ... | computer science |
37,537 | Abstractions for AI-Based User Interfaces and Systems | cs.PL | Novel user interfaces based on artificial intelligence, such as
natural-language agents, present new categories of engineering challenges.
These systems need to cope with uncertainty and ambiguity, interface with
machine learning algorithms, and compose information from multiple users to
make decisions. We propose to t... | computer science |
37,538 | Transforming Cooling Optimization for Green Data Center via Deep
Reinforcement Learning | cs.AI | Cooling system plays a key role in modern data center. Developing an optimal
control policy for data center cooling system is a challenging task. The
prevailing approaches often rely on approximated system models that are built
upon the knowledge of mechanical cooling, electrical and thermal management,
which is diffic... | computer science |
37,539 | A Streaming Accelerator for Deep Convolutional Neural Networks with
Image and Feature Decomposition for Resource-limited System Applications | cs.AR | Deep convolutional neural networks (CNN) are widely used in modern artificial
intelligence (AI) and smart vision systems but also limited by computation
latency, throughput, and energy efficiency on a resource-limited scenario, such
as mobile devices, internet of things (IoT), unmanned aerial vehicles (UAV),
and so on.... | computer science |
37,540 | LoIDE: a web-based IDE for Logic Programming - Preliminary Technical
Report | cs.SE | Logic-based paradigms are nowadays widely used in many different fields, also
thank to the availability of robust tools and systems that allow the
development of real-world and industrial applications.
In this work we present LoIDE, an advanced and modular web-editor for
logic-based languages that also integrates wit... | computer science |
37,541 | Process-oriented Iterative Multiple Alignment for Medical Process Mining | cs.DS | Adapted from biological sequence alignment, trace alignment is a process
mining technique used to visualize and analyze workflow data. Any analysis done
with this method, however, is affected by the alignment quality. The best
existing trace alignment techniques use progressive guide-trees to
heuristically approximate ... | computer science |
37,542 | Markov Brains: A Technical Introduction | cs.AI | Markov Brains are a class of evolvable artificial neural networks (ANN). They
differ from conventional ANNs in many aspects, but the key difference is that
instead of a layered architecture, with each node performing the same function,
Markov Brains are networks built from individual computational components.
These com... | computer science |
37,543 | The shortest way to visit all metro lines in Paris | cs.AI | What if $\{$a tourist, a train addict, Dr. Sheldon Cooper, somebody who likes
to waste time$\}$ wants to visit all metro lines or carriages in a given
network in a minimum number of steps? We study this problem with an application
to the Parisian metro network and propose optimal solutions thanks to
mathematical progra... | computer science |
37,544 | DropoutDAgger: A Bayesian Approach to Safe Imitation Learning | cs.AI | While imitation learning is becoming common practice in robotics, this
approach often suffers from data mismatch and compounding errors. DAgger is an
iterative algorithm that addresses these issues by continually aggregating
training data from both the expert and novice policies, but does not consider
the impact of saf... | computer science |
37,545 | On the Complexity of Robust Stable Marriage | cs.CC | Robust Stable Marriage (RSM) is a variant of the classical Stable Marriage
problem, where the robustness of a given stable matching is measured by the
number of modifications required for repairing it in case an unforeseen event
occurs. We focus on the complexity of finding an (a,b)-supermatch. An
(a,b)-supermatch is d... | computer science |
37,546 | A Comparative Quantitative Analysis of Contemporary Big Data Clustering
Algorithms for Market Segmentation in Hospitality Industry | cs.DB | The hospitality industry is one of the data-rich industries that receives
huge Volumes of data streaming at high Velocity with considerably Variety,
Veracity, and Variability. These properties make the data analysis in the
hospitality industry a big data problem. Meeting the customers' expectations is
a key factor in t... | computer science |
37,547 | Deep Reinforcement Learning for Event-Driven Multi-Agent Decision
Processes | cs.AI | The incorporation of macro-actions (temporally extended actions) into
multi-agent decision problems has the potential to address the curse of
dimensionality associated with such decision problems. Since macro-actions last
for stochastic durations, multiple agents executing decentralized policies in
cooperative environm... | computer science |
37,548 | Deep Reinforcement Learning for Dexterous Manipulation with Concept
Networks | cs.AI | Deep reinforcement learning yields great results for a large array of
problems, but models are generally retrained anew for each new problem to be
solved. Prior learning and knowledge are difficult to incorporate when training
new models, requiring increasingly longer training as problems become more
complex. This is e... | computer science |
37,549 | A Deep-Reinforcement Learning Approach for Software-Defined Networking
Routing Optimization | cs.NI | In this paper we design and evaluate a Deep-Reinforcement Learning agent that
optimizes routing. Our agent adapts automatically to current traffic conditions
and proposes tailored configurations that attempt to minimize the network
delay. Experiments show very promising performance. Moreover, this approach
provides imp... | computer science |
37,550 | Practical Machine Learning for Cloud Intrusion Detection: Challenges and
the Way Forward | cs.CR | Operationalizing machine learning based security detections is extremely
challenging, especially in a continuously evolving cloud environment.
Conventional anomaly detection does not produce satisfactory results for
analysts that are investigating security incidents in the cloud. Model
evaluation alone presents its own... | computer science |
37,551 | Non-Depth-First Search against Independent Distributions on an AND-OR
Tree | cs.DS | Suzuki and Niida (Ann. Pure. Appl. Logic, 2015) showed the following results
on independent distributions (IDs) on an AND-OR tree, where they took only
depth-first algorithms into consideration. (1) Among IDs such that probability
of the root having value 0 is fixed as a given r such that 0 < r < 1, if d is a
maximizer... | computer science |
37,552 | Complexity of Scheduling Charging in the Smart Grid | cs.CC | In the smart grid, the intent is to use flexibility in demand, both to
balance demand and supply as well as to resolve potential congestion. A first
prominent example of such flexible demand is the charging of electric vehicles,
which do not necessarily need to be charged as soon as they are plugged in. The
problem of ... | computer science |
37,553 | Defining a Lingua Franca to Open the Black Box of a Naïve Bayes
Recommender | cs.IR | Many AI systems have a black box nature that makes it difficult to understand
how they make their recommendations. This can be unsettling, as the designer
cannot be certain how the system will respond to novelty. To penetrate our
Na\"ive Bayes recommender's black box, we first asked, what do we want to know
from our sy... | computer science |
37,554 | OptLayer - Practical Constrained Optimization for Deep Reinforcement
Learning in the Real World | cs.RO | While deep reinforcement learning techniques have recently produced
considerable achievements on many decision-making problems, their use in
robotics has largely been limited to simulated worlds or restricted motions,
since unconstrained trial-and-error interactions in the real world can have
undesirable consequences f... | computer science |
37,555 | Efficiently Discovering Locally Exceptional yet Globally Representative
Subgroups | cs.DB | Subgroup discovery is a local pattern mining technique to find interpretable
descriptions of sub-populations that stand out on a given target variable. That
is, these sub-populations are exceptional with regard to the global
distribution. In this paper we argue that in many applications, such as
scientific discovery, s... | computer science |
37,556 | Towards Classification of Web ontologies using the Horizontal and
Vertical Segmentation | cs.AI | The new era of the Web is known as the semantic Web or the Web of data. The
semantic Web depends on ontologies that are seen as one of its pillars. The
bigger these ontologies, the greater their exploitation. However, when these
ontologies become too big other problems may appear, such as the complexity to
charge big f... | computer science |
37,557 | Autonomous Agents Modelling Other Agents: A Comprehensive Survey and
Open Problems | cs.AI | Much research in artificial intelligence is concerned with the development of
autonomous agents that can interact effectively with other agents. An important
aspect of such agents is the ability to reason about the behaviours of other
agents, by constructing models which make predictions about various properties
of int... | computer science |
37,558 | Intrusions in Marked Renewal Processes | cs.AI | We present a probabilistic model of an intrusion in a marked renewal process.
Given a process and a sequence of events, an intrusion is a subsequence of
events that is not produced by the process. Applications of the model are, for
example, online payment fraud with the fraudster taking over a user's account
and perfor... | computer science |
37,559 | Learning Unmanned Aerial Vehicle Control for Autonomous Target Following | cs.AI | While deep reinforcement learning (RL) methods have achieved unprecedented
successes in a range of challenging problems, their applicability has been
mainly limited to simulation or game domains due to the high sample complexity
of the trial-and-error learning process. However, real-world robotic
applications often nee... | computer science |
37,560 | Bayesian Filtering for ODEs with Bounded Derivatives | cs.NA | Recently there has been increasing interest in probabilistic solvers for
ordinary differential equations (ODEs) that return full probability measures,
instead of point estimates, over the solution and can incorporate uncertainty
over the ODE at hand, e.g. if the vector field or the initial value is only
approximately k... | computer science |
37,561 | Ensemble Classifier for Eye State Classification using EEG Signals | cs.AI | The growing importance and utilization of measuring brain waves (e.g. EEG
signals of eye state) in brain-computer interface (BCI) applications
highlighted the need for suitable classification methods. In this paper, a
comparison between three of well-known classification methods (i.e. support
vector machine (SVM), hidd... | computer science |
37,562 | A Simple Reinforcement Learning Mechanism for Resource Allocation in
LTE-A Networks with Markov Decision Process and Q-Learning | cs.AI | Resource allocation is still a difficult issue to deal with in wireless
networks. The unstable channel condition and traffic demand for Quality of
Service (QoS) raise some barriers that interfere with the process. It is
significant that an optimal policy takes into account some resources available
to each traffic class... | computer science |
37,563 | Traffic Optimization For a Mixture of Self-interested and Compliant
Agents | cs.MA | This paper focuses on two commonly used path assignment policies for agents
traversing a congested network: self-interested routing, and system-optimum
routing. In the self-interested routing policy each agent selects a path that
optimizes its own utility, while the system-optimum routing agents are assigned
paths with... | computer science |
37,564 | Case Study: Explaining Diabetic Retinopathy Detection Deep CNNs via
Integrated Gradients | cs.AI | In this report, we applied integrated gradients to explaining a neural
network for diabetic retinopathy detection. The integrated gradient is an
attribution method which measures the contributions of input to the quantity of
interest. We explored some new ways for applying this method such as explaining
intermediate la... | computer science |
37,565 | Personalized Fuzzy Text Search Using Interest Prediction and Word
Vectorization | cs.IR | In this paper we study the personalized text search problem. The keyword
based search method in conventional algorithms has a low efficiency in
understanding users' intention since the semantic meaning, user profile, user
interests are not always considered. Firstly, we propose a novel text search
algorithm using a inv... | computer science |
37,566 | Creating a Social Brain for Cooperative Connected Autonomous Vehicles:
Issues and Challenges | cs.AI | The connected autonomous vehicle has been often touted as a technology that
will become pervasive in society in the near future. Rather than being stand
alone, we examine the need for autonomous vehicles to cooperate and interact
within their socio-cyber-physical environments, including the problems
cooperation will so... | computer science |
37,567 | The Dutch's Real World Financial Institute: Introducing Quantum-Like
Bayesian Networks as an Alternative Model to deal with Uncertainty | cs.AI | In this work, we analyse and model a real life financial loan application
belonging to a sample bank in the Netherlands. The log is robust in terms of
data, containing a total of 262 200 event logs, belonging to 13 087 different
credit applications. The dataset is heterogeneous and consists of a mixture of
computer gen... | computer science |
37,568 | Supervised Q-walk for Learning Vector Representation of Nodes in
Networks | cs.SI | Automatic feature learning algorithms are at the forefront of modern day
machine learning research. We present a novel algorithm, supervised Q-walk,
which applies Q-learning to generate random walks on graphs such that the walks
prove to be useful for learning node features suitable for tackling with the
node classific... | computer science |
37,569 | Geo-referencing Place from Everyday Natural Language Descriptions | cs.AI | Natural language place descriptions in everyday communication provide a rich
source of spatial knowledge about places. An important step to utilize such
knowledge in information systems is geo-referencing all the places referred to
in these descriptions. Current techniques for geo-referencing places from text
documents... | computer science |
37,570 | On Preemption and Overdetermination in Formal Theories of Causality | cs.AI | One of the key challenges when looking for the causes of a complex event is
to determine the causal status of factors that are neither individually
necessary nor individually sufficient to produce that event. In order to reason
about how such factors should be taken into account, we need a vocabulary to
distinguish dif... | computer science |
37,571 | Counterfactual Causality from First Principles? | cs.LO | In this position paper we discuss three main shortcomings of existing
approaches to counterfactual causality from the computer science perspective,
and sketch lines of work to try and overcome these issues: (1) causality
definitions should be driven by a set of precisely specified requirements
rather than specific exam... | computer science |
37,572 | Prior Knowledge based mutation prioritization towards causal variant
finding in rare disease | cs.AI | How do we determine the mutational effects in exome sequencing data with
little or no statistical evidence? Can protein structural information fill in
the gap of not having enough statistical evidence? In this work, we answer the
two questions with the goal towards determining pathogenic effects of rare
variants in rar... | computer science |
37,573 | Day-Ahead Solar Forecasting Based on Multi-level Solar Measurements | cs.CE | The growing proliferation in solar deployment, especially at distribution
level, has made the case for power system operators to develop more accurate
solar forecasting models. This paper proposes a solar photovoltaic (PV)
generation forecasting model based on multi-level solar measurements and
utilizing a nonlinear au... | computer science |
37,574 | Exploring Cross-Domain Data Dependencies for Smart Homes to Improve
Energy Efficiency | cs.CY | Over the past decade, the idea of smart homes has been conceived as a
potential solution to counter energy crises or to at least mitigate its
intensive destructive consequences in the residential building sector. | computer science |
37,575 | Arguing Machines: Perception-Control System Redundancy and Edge Case
Discovery in Real-World Autonomous Driving | cs.AI | Safe autonomous driving may be one of the most difficult engineering
challenges that any artificial intelligence system has been asked to do since
the birth of AI over sixty years ago. The difficulty is not within the task
itself, but rather in the extremely small margin of allowable error given the
human life at stake... | computer science |
37,576 | Clusters of Driving Behavior from Observational Smartphone Data | cs.AI | Understanding driving behaviors is essential for improving safety and
mobility of our transportation systems. Data is usually collected via
simulator-based studies or naturalistic driving studies. Those techniques allow
for understanding relations between demographics, road conditions and safety.
On the other hand, the... | computer science |
37,577 | Fast Top-k Area Topics Extraction with Knowledge Base | cs.AI | What are the most popular research topics in Artificial Intelligence (AI)? We
formulate the problem as extracting top-$k$ topics that can best represent a
given area with the help of knowledge base. We theoretically prove that the
problem is NP-hard and propose an optimization model, FastKATE, to address this
problem b... | computer science |
37,578 | On the Ontological Modeling of Trees | cs.AI | Trees -- i.e., the type of data structure known under this name -- are
central to many aspects of knowledge organization. We investigate some central
design choices concerning the ontological modeling of such trees. In
particular, we consider the limits of what is expressible in the Web Ontology
Language, and provide a... | computer science |
37,579 | On Hashing-Based Approaches to Approximate DNF-Counting | cs.LO | Propositional model counting is a fundamental problem in artificial
intelligence with a wide variety of applications, such as probabilistic
inference, decision making under uncertainty, and probabilistic databases.
Consequently, the problem is of theoretical as well as practical interest. When
the constraints are expre... | computer science |
37,580 | Multi-Value Rule Sets | cs.AI | We present the Multi-vAlue Rule Set (MARS) model for interpretable
classification with feature efficient presentations. MARS introduces a more
generalized form of association rules that allows multiple values in a
condition. Rules of this form are more concise than traditional single-valued
rules in capturing and descr... | computer science |
37,581 | The Complete Extensions do not form a Complete Semilattice | cs.AI | In his seminal paper that inaugurated abstract argumentation, Dung proved
that the set of complete extensions forms a complete semilattice with respect
to set inclusion. In this note we demonstrate that this proof is incorrect with
counterexamples. We then trace the error in the proof and explain why it arose.
We then ... | computer science |
37,582 | Toward Crowd-Sensitive Path Planning | cs.AI | If a robot can predict crowds in parts of its environment that are
inaccessible to its sensors, then it can plan to avoid them. This paper
proposes a fast, online algorithm that learns average crowd densities in
different areas. It also describes how these densities can be incorporated into
existing navigation architec... | computer science |
37,583 | Mining Frequent Patterns in Process Models | cs.AI | Process mining has emerged as a way to analyze the behavior of an
organization by extracting knowledge from event logs and by offering techniques
to discover, monitor and enhance real processes. In the discovery of process
models, retrieving a complex one, i.e., a hardly readable process model, can
hinder the extractio... | computer science |
37,584 | Neuro Fuzzy Modelling for Prediction of Consumer Price Index | cs.CY | Economic indicators such as Consumer Price Index (CPI) have frequently used
in predicting future economic wealth for financial policy makers of respective
country. Most central banks, on guidelines of research studies, have recently
adopted an inflation targeting monetary policy regime, which accounts for high
requirem... | computer science |
37,585 | Safe Medicine Recommendation via Medical Knowledge Graph Embedding | cs.IR | Most of the existing medicine recommendation systems that are mainly based on
electronic medical records (EMRs) are significantly assisting doctors to make
better clinical decisions benefiting both patients and caregivers. Even though
the growth of EMRs is at a lighting fast speed in the era of big data, content
limita... | computer science |
37,586 | Reply With: Proactive Recommendation of Email Attachments | cs.IR | Email responses often contain items-such as a file or a hyperlink to an
external document-that are attached to or included inline in the body of the
message. Analysis of an enterprise email corpus reveals that 35% of the time
when users include these items as part of their response, the attachable item
is already prese... | computer science |
37,587 | Near-Optimal Adversarial Policy Switching for Decentralized Asynchronous
Multi-Agent Systems | cs.AI | A key challenge in multi-robot and multi-agent systems is generating
solutions that are robust to other self-interested or even adversarial parties
who actively try to prevent the agents from achieving their goals. The
practicality of existing works addressing this challenge is limited to only
small-scale synchronous d... | computer science |
37,588 | Deceased Organ Matching in Australia | cs.GT | Despite efforts to increase the supply of organs from living donors, most
kidney transplants performed in Australia still come from deceased donors. The
age of these donated organs has increased substantially in recent decades as
the rate of fatal accidents on roads has fallen. The Organ and Tissue Authority
in Austral... | computer science |
37,589 | Graph Embedding with Rich Information through Heterogeneous Network | cs.AI | Graph embedding has attracted increasing attention due to its critical
application in social network analysis. Most existing algorithms for graph
embedding only rely on the typology information and fail to use the copious
information in nodes as well as edges. As a result, their performance for many
tasks may not be sa... | computer science |
37,590 | Swift Linked Data Miner: Mining OWL 2 EL class expressions directly from
online RDF datasets | cs.AI | In this study, we present Swift Linked Data Miner, an interruptible algorithm
that can directly mine an online Linked Data source (e.g., a SPARQL endpoint)
for OWL 2 EL class expressions to extend an ontology with new SubClassOf:
axioms. The algorithm works by downloading only a small part of the Linked Data
source at ... | computer science |
37,591 | A Two-Phase Safe Vehicle Routing and Scheduling Problem: Formulations
and Solution Algorithms | cs.AI | We propose a two phase time dependent vehicle routing and scheduling
optimization model that identifies the safest routes, as a substitute for the
classical objectives given in the literature such as shortest distance or
travel time, through (1) avoiding recurring congestions, and (2) selecting
routes that have a lower... | computer science |
37,592 | Solving the "false positives" problem in fraud prediction | cs.AI | In this paper, we present an automated feature engineering based approach to
dramatically reduce false positives in fraud prediction. False positives plague
the fraud prediction industry. It is estimated that only 1 in 5 declared as
fraud are actually fraud and roughly 1 in every 6 customers have had a valid
transactio... | computer science |
37,593 | The Complexity of Graph-Based Reductions for Reachability in Markov
Decision Processes | cs.LO | We study the never-worse relation (NWR) for Markov decision processes with an
infinite-horizon reachability objective. A state q is never worse than a state
p if the maximal probability of reaching the target set of states from p is at
most the same value from q, regard- less of the probabilities labelling the
transiti... | computer science |
37,594 | Probabilistic Pursuits on Graphs | cs.DM | We consider discrete dynamical systems of "ant-like" agents engaged in a
sequence of pursuits on a graph environment. The agents emerge one by one at
equal time intervals from a source vertex $s$ and pursue each other by greedily
attempting to close the distance to their immediate predecessor, the agent that
emerged ju... | computer science |
37,596 | Multi-Objective Approaches to Markov Decision Processes with Uncertain
Transition Parameters | cs.AI | Markov decision processes (MDPs) are a popular model for performance analysis
and optimization of stochastic systems. The parameters of stochastic behavior
of MDPs are estimates from empirical observations of a system; their values are
not known precisely. Different types of MDPs with uncertain, imprecise or
bounded tr... | computer science |
37,597 | Sufficient and necessary causation are dual | cs.AI | Causation has been the issue of philosophic debate since Hippocrates. Recent
work defines actual causation in terms of Pearl/Halpern's causality framework,
formalizing necessary causes (IJCAI'15). This has inspired causality notions in
the security domain (CSF'15), which, perhaps surprisingly, formalize sufficient
caus... | computer science |
37,598 | Audiovisual Analytics Vocabulary and Ontology (AAVO): initial core and
example expansion | cs.CY | Visual Analytics might be defined as data mining assisted by interactive
visual interfaces. The field has been receiving prominent consideration by
researchers, developers and the industry. The literature, however, is complex
because it involves multiple fields of knowledge and is considerably recent. In
this article w... | computer science |
37,599 | Convolutional neural networks on irregular domains through approximate
translations on inferred graphs | cs.DM | We propose a generalization of convolutional neural networks (CNNs) to
irregular domains, through the use of an inferred graph structure. In more
details, we introduce a three-step methodology to create convolutional layers
that are adapted to the signals to process: 1) From a training set of signals,
infer a graph rep... | computer science |
37,600 | An Ontology to support automated negotiation | cs.AI | In this work we propose an ontology to support automated negotiation in
multiagent systems. The ontology can be connected with some domain-specific
ontologies to facilitate the negotiation in different domains, such as
Intelligent Transportation Systems (ITS), e-commerce, etc. The specific
negotiation rules for each ty... | computer science |
37,601 | Long-Distance Loop Closure Using General Object Landmarks | cs.RO | Visual localization under large changes in scale is an important capability
in many robotic mapping applications, such as localizing at low altitudes in
maps built at high altitudes, or performing loop closure over long distances.
Existing approaches, however, are robust only up to a 3x difference in scale
between map ... | computer science |
37,602 | Vehicle Routing Problem with Vector Profits (VRPVP) with Max-Min
Criterion | math.OC | This paper introduces a new routing problem referred to as the vehicle
routing problem with vector profits. Given a network composed of nodes
(depot/sites) and arcs connecting the nodes, the problem determines routes that
depart from the depot, visit sites to collect profits, and return to the depot.
There are multiple... | computer science |
37,603 | Improve SAT-solving with Machine Learning | cs.AI | In this project, we aimed to improve the runtime of Minisat, a
Conflict-Driven Clause Learning (CDCL) solver that solves the Propositional
Boolean Satisfiability (SAT) problem. We first used a logistic regression model
to predict the satisfiability of propositional boolean formulae after fixing
the values of a certain ... | computer science |
37,604 | SemTK: An Ontology-first, Open Source Semantic Toolkit for Managing and
Querying Knowledge Graphs | cs.AI | The relatively recent adoption of Knowledge Graphs as an enabling technology
in multiple high-profile artificial intelligence and cognitive applications has
led to growing interest in the Semantic Web technology stack. Many
semantics-related tools, however, are focused on serving experts with a deep
understanding of se... | computer science |
37,605 | Building Data-driven Models with Microstructural Images: Generalization
and Interpretability | cs.AI | As data-driven methods rise in popularity in materials science applications,
a key question is how these machine learning models can be used to understand
microstructure. Given the importance of process-structure-property relations
throughout materials science, it seems logical that models that can leverage
microstruct... | computer science |
37,606 | Early prediction of the duration of protests using probabilistic Latent
Dirichlet Allocation and Decision Trees | cs.SI | Protests and agitations are an integral part of every democratic civil
society. In recent years, South Africa has seen a large increase in its
protests. The objective of this paper is to provide an early prediction of the
duration of protests from its free flowing English text description. Free
flowing descriptions of ... | computer science |
37,607 | School bus routing by maximizing trip compatibility | math.OC | School bus planning is usually divided into routing and scheduling due to the
complexity of solving them concurrently. However, the separation between these
two steps may lead to worse solutions with higher overall costs than that from
solving them together. When finding the minimal number of trips in the routing
probl... | computer science |
37,608 | An iterative school decomposition algorithm for solving the multi-school
bus routing and scheduling problem | math.OC | Servicing the school transportation demand safely with a minimum number of
buses is one of the highest financial goals for school transportation
directors. To achieve that objective, a good and efficient way to solve the
routing and scheduling problem is required. Due to the growth of the computing
power, the spotlight... | computer science |
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