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20,402 | Solving stable matching problems using answer set programming | cs.AI | Since the introduction of the stable marriage problem (SMP) by Gale and
Shapley (1962), several variants and extensions have been investigated. While
this variety is useful to widen the application potential, each variant
requires a new algorithm for finding the stable matchings. To address this
issue, we propose an en... | computer science |
20,403 | Deep Active Object Recognition by Joint Label and Action Prediction | cs.AI | An active object recognition system has the advantage of being able to act in
the environment to capture images that are more suited for training and that
lead to better performance at test time. In this paper, we propose a deep
convolutional neural network for active object recognition that simultaneously
predicts the... | computer science |
20,404 | A thermodynamical approach towards multi-criteria decision making (MCDM) | cs.AI | In multi-criteria decision making (MCDM) problems, ratings are assigned to
the alternatives on different criteria by the expert group. In this paper, we
propose a thermodynamically consistent model for MCDM using the analogies for
thermodynamical indicators - energy, exergy and entropy. The most commonly used
method fo... | computer science |
20,405 | Learning the Preferences of Ignorant, Inconsistent Agents | cs.AI | An important use of machine learning is to learn what people value. What
posts or photos should a user be shown? Which jobs or activities would a person
find rewarding? In each case, observations of people's past choices can inform
our inferences about their likes and preferences. If we assume that choices are
approxim... | computer science |
20,406 | Modeling Progress in AI | cs.AI | Participants in recent discussions of AI-related issues ranging from
intelligence explosion to technological unemployment have made diverse claims
about the nature, pace, and drivers of progress in AI. However, these theories
are rarely specified in enough detail to enable systematic evaluation of their
assumptions or ... | computer science |
20,407 | Test-Driven Development of ontologies (extended version) | cs.AI | Emerging ontology authoring methods to add knowledge to an ontology focus on
ameliorating the validation bottleneck. The verification of the newly added
axiom is still one of trying and seeing what the reasoner says, because a
systematic testbed for ontology authoring is missing. We sought to address this
by introducin... | computer science |
20,408 | Multivariate Time Series Classification Using Dynamic Time Warping
Template Selection for Human Activity Recognition | cs.AI | Accurate and computationally efficient means for classifying human activities
have been the subject of extensive research efforts. Most current research
focuses on extracting complex features to achieve high classification accuracy.
We propose a template selection approach based on Dynamic Time Warping, such
that compl... | computer science |
20,409 | Beauty and Brains: Detecting Anomalous Pattern Co-Occurrences | cs.AI | Our world is filled with both beautiful and brainy people, but how often does
a Nobel Prize winner also wins a beauty pageant? Let us assume that someone who
is both very beautiful and very smart is more rare than what we would expect
from the combination of the number of beautiful and brainy people. Of course
there wi... | computer science |
20,410 | Keeping it Short and Simple: Summarising Complex Event Sequences with
Multivariate Patterns | cs.AI | We study how to obtain concise descriptions of discrete multivariate
sequential data. In particular, how to do so in terms of rich multivariate
sequential patterns that can capture potentially highly interesting
(cor)relations between sequences. To this end we allow our pattern language to
span over the domains (alphab... | computer science |
20,411 | Heuristic algorithms for finding distribution reducts in probabilistic
rough set model | cs.AI | Attribute reduction is one of the most important topics in rough set theory.
Heuristic attribute reduction algorithms have been presented to solve the
attribute reduction problem. It is generally known that fitness functions play
a key role in developing heuristic attribute reduction algorithms. The
monotonicity of fit... | computer science |
20,412 | Measuring pattern retention in anonymized data -- where one measure is
not enough | cs.AI | In this paper, we explore how modifying data to preserve privacy affects the
quality of the patterns discoverable in the data. For any analysis of modified
data to be worth doing, the data must be as close to the original as possible.
Therein lies a problem -- how does one make sure that modified data still
contains th... | computer science |
20,413 | Probabilistic Model-Based Approach for Heart Beat Detection | cs.AI | Nowadays, hospitals are ubiquitous and integral to modern society. Patients
flow in and out of a veritable whirlwind of paperwork, consultations, and
potential inpatient admissions, through an abstracted system that is not
without flaws. One of the biggest flaws in the medical system is perhaps an
unexpected one: the p... | computer science |
20,414 | Toward a Research Agenda in Adversarial Reasoning: Computational
Approaches to Anticipating the Opponent's Intent and Actions | cs.AI | This paper defines adversarial reasoning as computational approaches to
inferring and anticipating an enemy's perceptions, intents and actions. It
argues that adversarial reasoning transcends the boundaries of game theory and
must also leverage such disciplines as cognitive modeling, control theory, AI
planning and oth... | computer science |
20,415 | Using Data Analytics to Detect Anomalous States in Vehicles | cs.AI | Vehicles are becoming more and more connected, this opens up a larger attack
surface which not only affects the passengers inside vehicles, but also people
around them. These vulnerabilities exist because modern systems are built on
the comparatively less secure and old CAN bus framework which lacks even basic
authenti... | computer science |
20,416 | Mining Massive Hierarchical Data Using a Scalable Probabilistic
Graphical Model | cs.AI | Probabilistic Graphical Models (PGM) are very useful in the fields of machine
learning and data mining. The crucial limitation of those models,however, is
the scalability. The Bayesian Network, which is one of the most common PGMs
used in machine learning and data mining, demonstrates this limitation when the
training ... | computer science |
20,417 | Conditional probability generation methods for high reliability
effects-based decision making | cs.AI | Decision making is often based on Bayesian networks. The building blocks for
Bayesian networks are its conditional probability tables (CPTs). These tables
are obtained by parameter estimation methods, or they are elicited from subject
matter experts (SME). Some of these knowledge representations are insufficient
approx... | computer science |
20,418 | Combining Fuzzy Cognitive Maps and Discrete Random Variables | cs.AI | In this paper we propose an extension to the Fuzzy Cognitive Maps (FCMs) that
aims at aggregating a number of reasoning tasks into a one parallel run. The
described approach consists in replacing real-valued activation levels of
concepts (and further influence weights) by random variables. Such extension,
followed by t... | computer science |
20,419 | Modeling Variations of First-Order Horn Abduction in Answer Set
Programming | cs.AI | We study abduction in First Order Horn logic theories where all atoms can be
abduced and we are looking for preferred solutions with respect to three
objective functions: cardinality minimality, coherence, and weighted abduction.
We represent this reasoning problem in Answer Set Programming (ASP), in order
to obtain a ... | computer science |
20,420 | Evaluating Go Game Records for Prediction of Player Attributes | cs.AI | We propose a way of extracting and aggregating per-move evaluations from sets
of Go game records. The evaluations capture different aspects of the games such
as played patterns or statistic of sente/gote sequences. Using machine learning
algorithms, the evaluations can be utilized to predict different relevant
target v... | computer science |
20,421 | A Notation for Markov Decision Processes | cs.AI | This paper specifies a notation for Markov decision processes. | computer science |
20,422 | Evolving Non-linear Stacking Ensembles for Prediction of Go Player
Attributes | cs.AI | The paper presents an application of non-linear stacking ensembles for
prediction of Go player attributes. An evolutionary algorithm is used to form a
diverse ensemble of base learners, which are then aggregated by a stacking
ensemble. This methodology allows for an efficient prediction of different
attributes of Go pl... | computer science |
20,423 | Benders Decomposition for the Design of a Hub and Shuttle Public Transit
System | cs.AI | The BusPlus project aims at improving the off-peak hours public transit
service in Canberra, Australia. To address the difficulty of covering a large
geographic area, BusPlus proposes a hub and shuttle model consisting of a
combination of a few high-frequency bus routes between key hubs and a large
number of shuttles t... | computer science |
20,424 | Programming in logic without logic programming | cs.AI | In previous work, we proposed a logic-based framework in which computation is
the execution of actions in an attempt to make reactive rules of the form if
antecedent then consequent true in a canonical model of a logic program
determined by an initial state, sequence of events, and the resulting sequence
of subsequent ... | computer science |
20,425 | Artwork creation by a cognitive architecture integrating computational
creativity and dual process approaches | cs.AI | The paper proposes a novel cognitive architecture (CA) for computational
creativity based on the Psi model and on the mechanisms inspired by dual
process theories of reasoning and rationality. In recent years, many cognitive
models have focused on dual process theories to better describe and implement
complex cognitive... | computer science |
20,426 | Fuzzy Object-Oriented Dynamic Networks. I | cs.AI | The concepts of fuzzy objects and their classes are described that make it
possible to structurally represent knowledge about fuzzy and partially-defined
objects and their classes. Operations over such objects and classes are also
proposed that make it possible to obtain sets and new classes of fuzzy objects
and also t... | computer science |
20,427 | Basic Reasoning with Tensor Product Representations | cs.AI | In this paper we present the initial development of a general theory for
mapping inference in predicate logic to computation over Tensor Product
Representations (TPRs; Smolensky (1990), Smolensky & Legendre (2006)). After an
initial brief synopsis of TPRs (Section 0), we begin with particular examples
of inference with... | computer science |
20,428 | Essence' Description | cs.AI | A description of the Essence' language as used by the tool Savile Row. | computer science |
20,429 | An Application of the Generalized Rectangular Fuzzy Model to Critical
Thinking Assessment | cs.AI | The authors apply the Generalized Rectangular Model to assessing critical
thinking skills and its relations with their language competency. | computer science |
20,430 | A Method for Image Reduction Based on a Generalization of Ordered
Weighted Averaging Functions | cs.AI | In this paper we propose a special type of aggregation function which
generalizes the notion of Ordered Weighted Averaging Function - OWA. The
resulting functions are called Dynamic Ordered Weighted Averaging Functions ---
DYOWAs. This generalization will be developed in such way that the weight
vectors are variables d... | computer science |
20,431 | Learning the Semantics of Structured Data Sources | cs.AI | Information sources such as relational databases, spreadsheets, XML, JSON,
and Web APIs contain a tremendous amount of structured data that can be
leveraged to build and augment knowledge graphs. However, they rarely provide a
semantic model to describe their contents. Semantic models of data sources
represent the impl... | computer science |
20,432 | SimpleDS: A Simple Deep Reinforcement Learning Dialogue System | cs.AI | This paper presents 'SimpleDS', a simple and publicly available dialogue
system trained with deep reinforcement learning. In contrast to previous
reinforcement learning dialogue systems, this system avoids manual feature
engineering by performing action selection directly from raw text of the last
system and (noisy) us... | computer science |
20,433 | Coalition-based Planning of Military Operations: Adversarial Reasoning
Algorithms in an Integrated Decision Aid | cs.AI | Use of knowledge-based planning tools can help alleviate the challenges of
planning a complex operation by a coalition of diverse parties in an
adversarial environment. We explore these challenges and potential
contributions of knowledge-based tools using as an example the CADET system, a
knowledge-based tool capable o... | computer science |
20,434 | Decision Aids for Adversarial Planning in Military Operations:
Algorithms, Tools, and Turing-test-like Experimental Validation | cs.AI | Use of intelligent decision aids can help alleviate the challenges of
planning complex operations. We describe integrated algorithms, and a tool
capable of translating a high-level concept for a tactical military operation
into a fully detailed, actionable plan, producing automatically (or with human
guidance) plans wi... | computer science |
20,435 | Towards Resolving Unidentifiability in Inverse Reinforcement Learning | cs.AI | We consider a setting for Inverse Reinforcement Learning (IRL) where the
learner is extended with the ability to actively select multiple environments,
observing an agent's behavior on each environment. We first demonstrate that if
the learner can experiment with any transition dynamics on some fixed set of
states and ... | computer science |
20,436 | Identification and classification of TCM syndrome types among patients
with vascular mild cognitive impairment using latent tree analysis | cs.AI | Objective: To treat patients with vascular mild cognitive impairment (VMCI)
using TCM, it is necessary to classify the patients into TCM syndrome types and
to apply different treatments to different types. We investigate how to
properly carry out the classification using a novel data-driven method known as
latent tree ... | computer science |
20,437 | Intelligent Conversational Bot for Massive Online Open Courses (MOOCs) | cs.AI | Massive Online Open Courses (MOOCs) which were introduced in 2008 has since
drawn attention around the world for both its advantages as well as criticism
on its drawbacks. One of the issues in MOOCs which is the lack of interactivity
with the instructor has brought conversational bot into the picture to fill in
this ga... | computer science |
20,438 | Multi-Object Reasoning with Constrained Goal Models | cs.AI | Goal models have been widely used in Computer Science to represent software
requirements, business objectives, and design qualities. Existing goal
modelling techniques, however, have shown limitations of expressiveness and/or
tractability in coping with complex real-world problems. In this work, we
exploit advances in ... | computer science |
20,439 | Learning and Tuning Meta-heuristics in Plan Space Planning | cs.AI | In recent years, the planning community has observed that techniques for
learning heuristic functions have yielded improvements in performance. One
approach is to use offline learning to learn predictive models from existing
heuristics in a domain dependent manner. These learned models are deployed as
new heuristic fun... | computer science |
20,440 | Probabilistic Models for Computerized Adaptive Testing: Experiments | cs.AI | This paper follows previous research we have already performed in the area of
Bayesian networks models for CAT. We present models using Item Response Theory
(IRT - standard CAT method), Bayesian networks, and neural networks. We
conducted simulated CAT tests on empirical data. Results of these tests are
presented for e... | computer science |
20,441 | Discussion on Mechanical Learning and Learning Machine | cs.AI | Mechanical learning is a computing system that is based on a set of simple
and fixed rules, and can learn from incoming data. A learning machine is a
system that realizes mechanical learning. Importantly, we emphasis that it is
based on a set of simple and fixed rules, contrasting to often called machine
learning that ... | computer science |
20,442 | Numerical Atrribute Extraction from Clinical Texts | cs.AI | This paper describes about information extraction system, which is an
extension of the system developed by team Hitachi for "Disease/Disorder
Template filling" task organized by ShARe/CLEF eHealth Evolution Lab 2014. In
this extension module we focus on extraction of numerical attributes and values
from discharge summa... | computer science |
20,443 | A Comparative Study of Ranking-based Semantics for Abstract
Argumentation | cs.AI | Argumentation is a process of evaluating and comparing a set of arguments. A
way to compare them consists in using a ranking-based semantics which
rank-order arguments from the most to the least acceptable ones. Recently, a
number of such semantics have been proposed independently, often associated
with some desirable ... | computer science |
20,444 | Finding the different patterns in buildings data using bag of words
representation with clustering | cs.AI | The understanding of the buildings operation has become a challenging task
due to the large amount of data recorded in energy efficient buildings. Still,
today the experts use visual tools for analyzing the data. In order to make the
task realistic, a method has been proposed in this paper to automatically
detect the d... | computer science |
20,445 | Fuzzy Object-Oriented Dynamic Networks. II | cs.AI | This article generalizes object-oriented dynamic networks to the fuzzy case,
which allows one to represent knowledge on objects and classes of objects that
are fuzzy by nature and also to model their changes in time. Within the
framework of the approach described, a mechanism is proposed that makes it
possible to acqui... | computer science |
20,446 | Wayfinding and cognitive maps for pedestrian models | cs.AI | Usually, routing models in pedestrian dynamics assume that agents have
fulfilled and global knowledge about the building's structure. However, they
neglect the fact that pedestrians possess no or only parts of information about
their position relative to final exits and possible routes leading to them. To
get a more re... | computer science |
20,447 | Probabilistic Extension to the Concurrent Constraint Factor Oracle Model
for Music Improvisation | cs.AI | We can program a Real-Time (RT) music improvisation system in C++ without a
formal semantic or we can model it with process calculi such as the
Non-deterministic Timed Concurrent Constraint (ntcc) calculus. "A Concurrent
Constraints Factor Oracle (FO) model for Music Improvisation" (Ccfomi) is an
improvisation model sp... | computer science |
20,448 | End-to-End Goal-Driven Web Navigation | cs.AI | We propose a goal-driven web navigation as a benchmark task for evaluating an
agent with abilities to understand natural language and plan on partially
observed environments. In this challenging task, an agent navigates through a
website, which is represented as a graph consisting of web pages as nodes and
hyperlinks a... | computer science |
20,449 | Adaptive imputation of missing values for incomplete pattern
classification | cs.AI | In classification of incomplete pattern, the missing values can either play a
crucial role in the class determination, or have only little influence (or
eventually none) on the classification results according to the context. We
propose a credal classification method for incomplete pattern with adaptive
imputation of m... | computer science |
20,450 | Time Resource Networks | cs.AI | The problem of scheduling under resource constraints is widely applicable.
One prominent example is power management, in which we have a limited
continuous supply of power but must schedule a number of power-consuming tasks.
Such problems feature tightly coupled continuous resource constraints and
continuous temporal c... | computer science |
20,451 | Detection of Cooperative Interactions in Logistic Regression Models | cs.AI | An important problem in the field of bioinformatics is to identify
interactive effects among profiled variables for outcome prediction. In this
paper, a logistic regression model with pairwise interactions among a set of
binary covariates is considered. Modeling the structure of the interactions by
a graph, our goal is... | computer science |
20,452 | BPCMont: Business Process Change Management Ontology | cs.AI | Change management for evolving collaborative business process development is
crucial when the business logic, transections and workflow change due to
changes in business strategies or organizational and technical environment.
During the change implementation, business processes are analyzed and improved
ensuring that t... | computer science |
20,453 | Extending Consequence-Based Reasoning to SRIQ | cs.AI | Consequence-based calculi are a family of reasoning algorithms for
description logics (DLs), and they combine hypertableau and resolution in a way
that often achieves excellent performance in practice. Up to now, however, they
were proposed for either Horn DLs (which do not support disjunction), or for
DLs without coun... | computer science |
20,454 | Towards reducing the multidimensionality of OLAP cubes using the
Evolutionary Algorithms and Factor Analysis Methods | cs.AI | Data Warehouses are structures with large amount of data collected from
heterogeneous sources to be used in a decision support system. Data Warehouses
analysis identifies hidden patterns initially unexpected which analysis
requires great memory and computation cost. Data reduction methods were
proposed to make this ana... | computer science |
20,455 | POMDP-lite for Robust Robot Planning under Uncertainty | cs.AI | The partially observable Markov decision process (POMDP) provides a
principled general model for planning under uncertainty. However, solving a
general POMDP is computationally intractable in the worst case. This paper
introduces POMDP-lite, a subclass of POMDPs in which the hidden state variables
are constant or only ... | computer science |
20,456 | Reinforcement Learning approach for Real Time Strategy Games Battle city
and S3 | cs.AI | In this paper we proposed reinforcement learning algorithms with the
generalized reward function. In our proposed method we use Q-learning and SARSA
algorithms with generalised reward function to train the reinforcement learning
agent. We evaluated the performance of our proposed algorithms on two real-time
strategy ga... | computer science |
20,457 | 11 x 11 Domineering is Solved: The first player wins | cs.AI | We have developed a program called MUDoS (Maastricht University Domineering
Solver) that solves Domineering positions in a very efficient way. This enables
the solution of known positions so far (up to the 10 x 10 board) much quicker
(measured in number of investigated nodes).
More importantly, it enables the solutio... | computer science |
20,458 | Query Answering with Inconsistent Existential Rules under Stable Model
Semantics | cs.AI | Traditional inconsistency-tolerent query answering in ontology-based data
access relies on selecting maximal components of an ABox/database which are
consistent with the ontology. However, some rules in ontologies might be
unreliable if they are extracted from ontology learning or written by
unskillful knowledge engine... | computer science |
20,459 | Applying Boolean discrete methods in the production of a real-valued
probabilistic programming model | cs.AI | In this paper we explore the application of some notable Boolean methods,
namely the Disjunctive Normal Form representation of logic table expansions,
and apply them to a real-valued logic model which utilizes quantities on the
range [0,1] to produce a probabilistic programming of a game character's logic
in mathematic... | computer science |
20,460 | A General Modifier-based Framework for Inconsistency-Tolerant Query
Answering | cs.AI | We propose a general framework for inconsistency-tolerant query answering
within existential rule setting. This framework unifies the main semantics
proposed by the state of art and introduces new ones based on cardinality and
majority principles. It relies on two key notions: modifiers and inference
strategies. An inc... | computer science |
20,461 | The Singularity May Never Be Near | cs.AI | There is both much optimism and pessimism around artificial intelligence (AI)
today. The optimists are investing millions of dollars, and even in some cases
billions of dollars into AI. The pessimists, on the other hand, predict that AI
will end many things: jobs, warfare, and even the human race. Both the
optimists an... | computer science |
20,462 | Computational Narrative Intelligence: A Human-Centered Goal for
Artificial Intelligence | cs.AI | Narrative intelligence is the ability to craft, tell, understand, and respond
affectively to stories. We argue that instilling artificial intelligences with
computational narrative intelligence affords a number of applications
beneficial to humans. We lay out some of the machine learning challenges
necessary to solve t... | computer science |
20,463 | Stochastic Shortest Path with Energy Constraints in POMDPs | cs.AI | We consider partially observable Markov decision processes (POMDPs) with a
set of target states and positive integer costs associated with every
transition. The traditional optimization objective (stochastic shortest path)
asks to minimize the expected total cost until the target set is reached. We
extend the tradition... | computer science |
20,464 | Time and Activity Sequence Prediction of Business Process Instances | cs.AI | The ability to know in advance the trend of running process instances, with
respect to different features, such as the expected completion time, would
allow business managers to timely counteract to undesired situations, in order
to prevent losses. Therefore, the ability to accurately predict future features
of running... | computer science |
20,465 | Toward Game Level Generation from Gameplay Videos | cs.AI | Algorithms that generate computer game content require game design knowledge.
We present an approach to automatically learn game design knowledge for level
design from gameplay videos. We further demonstrate how the acquired design
knowledge can be used to generate sections of game levels. Our approach
involves parsing... | computer science |
20,466 | Causal Discovery from Subsampled Time Series Data by Constraint
Optimization | cs.AI | This paper focuses on causal structure estimation from time series data in
which measurements are obtained at a coarser timescale than the causal
timescale of the underlying system. Previous work has shown that such
subsampling can lead to significant errors about the system's causal structure
if not properly taken int... | computer science |
20,467 | A Neutrosophic Recommender System for Medical Diagnosis Based on
Algebraic Neutrosophic Measures | cs.AI | Neutrosophic set has the ability to handle uncertain, incomplete,
inconsistent, indeterminate information in a more accurate way. In this paper,
we proposed a neutrosophic recommender system to predict the diseases based on
neutrosophic set which includes single-criterion neutrosophic recommender
system (SC-NRS) and mu... | computer science |
20,468 | Scalable Bayesian Rule Lists | cs.AI | We present an algorithm for building probabilistic rule lists that is two
orders of magnitude faster than previous work. Rule list algorithms are
competitors for decision tree algorithms. They are associative classifiers, in
that they are built from pre-mined association rules. They have a logical
structure that is a s... | computer science |
20,469 | Personalized and situation-aware multimodal route recommendations: the
FAVOUR algorithm | cs.AI | Route choice in multimodal networks shows a considerable variation between
different individuals as well as the current situational context.
Personalization of recommendation algorithms are already common in many areas,
e.g., online retail. However, most online routing applications still provide
shortest distance or sh... | computer science |
20,470 | Filter based Taxonomy Modification for Improving Hierarchical
Classification | cs.AI | Hierarchical Classification (HC) is a supervised learning problem where
unlabeled instances are classified into a taxonomy of classes. Several methods
that utilize the hierarchical structure have been developed to improve the HC
performance. However, in most cases apriori defined hierarchical structure by
domain expert... | computer science |
20,471 | Network Unfolding Map by Edge Dynamics Modeling | cs.AI | The emergence of collective dynamics in neural networks is a mechanism of the
animal and human brain for information processing. In this paper, we develop a
computational technique using distributed processing elements in a complex
network, which are called particles, to solve semi-supervised learning
problems. Three a... | computer science |
20,472 | GeoGebra Tools with Proof Capabilities | cs.AI | We report about significant enhancements of the complex algebraic geometry
theorem proving subsystem in GeoGebra for automated proofs in Euclidean
geometry, concerning the extension of numerous GeoGebra tools with proof
capabilities. As a result, a number of elementary theorems can be proven by
using GeoGebra's intuiti... | computer science |
20,473 | Learning Physical Intuition of Block Towers by Example | cs.AI | Wooden blocks are a common toy for infants, allowing them to develop motor
skills and gain intuition about the physical behavior of the world. In this
paper, we explore the ability of deep feed-forward models to learn such
intuitive physics. Using a 3D game engine, we create small towers of wooden
blocks whose stabilit... | computer science |
20,474 | A Linked Data Scalability Challenge: Concept Reuse Leads to Semantic
Decay | cs.AI | The increasing amount of available Linked Data resources is laying the
foundations for more advanced Semantic Web applications. One of their main
limitations, however, remains the general low level of data quality. In this
paper we focus on a measure of quality which is negatively affected by the
increase of the availa... | computer science |
20,475 | Learning to Blend Computer Game Levels | cs.AI | We present an approach to generate novel computer game levels that blend
different game concepts in an unsupervised fashion. Our primary contribution is
an analogical reasoning process to construct blends between level design models
learned from gameplay videos. The models represent probabilistic relationships
between ... | computer science |
20,476 | Hierarchical Linearly-Solvable Markov Decision Problems | cs.AI | We present a hierarchical reinforcement learning framework that formulates
each task in the hierarchy as a special type of Markov decision process for
which the Bellman equation is linear and has analytical solution. Problems of
this type, called linearly-solvable MDPs (LMDPs) have interesting properties
that can be ex... | computer science |
20,477 | A Set Theoretic Approach for Knowledge Representation: the
Representation Part | cs.AI | In this paper, we propose a set theoretic approach for knowledge
representation. While the syntax of an application domain is captured by set
theoretic constructs including individuals, concepts and operators, knowledge
is formalized by equality assertions. We first present a primitive form that
uses minimal assumed kn... | computer science |
20,478 | High-dimensional Black-box Optimization via Divide and Approximate
Conquer | cs.AI | Divide and Conquer (DC) is conceptually well suited to high-dimensional
optimization by decomposing a problem into multiple small-scale sub-problems.
However, appealing performance can be seldom observed when the sub-problems are
interdependent. This paper suggests that the major difficulty of tackling
interdependent s... | computer science |
20,479 | Penta and Hexa Valued Representation of Neutrosophic Information | cs.AI | Starting from the primary representation of neutrosophic information, namely
the degree of truth, degree of indeterminacy and degree of falsity, we define a
nuanced representation in a penta valued fuzzy space, described by the index of
truth, index of falsity, index of ignorance, index of contradiction and index
of he... | computer science |
20,480 | Geometry of Interest (GOI): Spatio-Temporal Destination Extraction and
Partitioning in GPS Trajectory Data | cs.AI | Nowadays large amounts of GPS trajectory data is being continuously collected
by GPS-enabled devices such as vehicles navigation systems and mobile phones.
GPS trajectory data is useful for applications such as traffic management,
location forecasting, and itinerary planning. Such applications often need to
extract the... | computer science |
20,481 | Controlling Search in Very large Commonsense Knowledge Bases: A Machine
Learning Approach | cs.AI | Very large commonsense knowledge bases (KBs) often have thousands to millions
of axioms, of which relatively few are relevant for answering any given query.
A large number of irrelevant axioms can easily overwhelm resolution-based
theorem provers. Therefore, methods that help the reasoner identify useful
inference path... | computer science |
20,482 | Characterization of neighborhood behaviours in a multi-neighborhood
local search algorithm | cs.AI | We consider a multi-neighborhood local search algorithm with a large number
of possible neighborhoods. Each neighborhood is accompanied by a weight value
which represents the probability of being chosen at each iteration. These
weights are fixed before the algorithm runs, and are considered as parameters
of the algorit... | computer science |
20,483 | Comparing Human and Automated Evaluation of Open-Ended Student Responses
to Questions of Evolution | cs.AI | Written responses can provide a wealth of data in understanding student
reasoning on a topic. Yet they are time- and labor-intensive to score,
requiring many instructors to forego them except as limited parts of summative
assessments at the end of a unit or course. Recent developments in Machine
Learning (ML) have prod... | computer science |
20,484 | Load Disaggregation Based on Aided Linear Integer Programming | cs.AI | Load disaggregation based on aided linear integer programming (ALIP) is
proposed. We start with a conventional linear integer programming (IP) based
disaggregation and enhance it in several ways. The enhancements include
additional constraints, correction based on a state diagram, median filtering,
and linear programmi... | computer science |
20,485 | Properties of ABA+ for Non-Monotonic Reasoning | cs.AI | We investigate properties of ABA+, a formalism that extends the well studied
structured argumentation formalism Assumption-Based Argumentation (ABA) with a
preference handling mechanism. In particular, we establish desirable properties
that ABA+ semantics exhibit. These pave way to the satisfaction by ABA+ of some
(arg... | computer science |
20,486 | Using Enthymemes to Fill the Gap between Logical Argumentation and
Revision of Abstract Argumentation Frameworks | cs.AI | In this paper, we present a preliminary work on an approach to fill the gap
between logic-based argumentation and the numerous approaches to tackle the
dynamics of abstract argumentation frameworks. Our idea is that, even when
arguments and attacks are defined by means of a logical belief base, there may
be some uncert... | computer science |
20,487 | Algorithms for Batch Hierarchical Reinforcement Learning | cs.AI | Hierarchical Reinforcement Learning (HRL) exploits temporal abstraction to
solve large Markov Decision Processes (MDP) and provide transferable subtask
policies. In this paper, we introduce an off-policy HRL algorithm: Hierarchical
Q-value Iteration (HQI). We show that it is possible to effectively learn
recursive opti... | computer science |
20,488 | Iterated Ontology Revision by Reinterpretation | cs.AI | Iterated applications of belief change operators are essential for different
scenarios such as that of ontology evolution where new information is not
presented at once but only in piecemeal fashion within a sequence. I discuss
iterated applications of so called reinterpretation operators that trace
conflicts between o... | computer science |
20,489 | Ordinal Conditional Functions for Nearly Counterfactual Revision | cs.AI | We are interested in belief revision involving conditional statements where
the antecedent is almost certainly false. To represent such problems, we use
Ordinal Conditional Functions that may take infinite values. We model belief
change in this context through simple arithmetical operations that allow us to
capture the... | computer science |
20,490 | Verifiability of Argumentation Semantics | cs.AI | Dung's abstract argumentation theory is a widely used formalism to model
conflicting information and to draw conclusions in such situations. Hereby, the
knowledge is represented by so-called argumentation frameworks (AFs) and the
reasoning is done via semantics extracting acceptable sets. All reasonable
semantics are b... | computer science |
20,491 | Distributing Knowledge into Simple Bases | cs.AI | Understanding the behavior of belief change operators for fragments of
classical logic has received increasing interest over the last years. Results
in this direction are mainly concerned with adapting representation theorems.
However, fragment-driven belief change also leads to novel research questions.
In this paper ... | computer science |
20,492 | A Survey of League Championship Algorithm: Prospects and Challenges | cs.AI | The League Championship Algorithm (LCA) is sport-inspired optimization
algorithm that was introduced by Ali Husseinzadeh Kashan in the year 2009. It
has since drawn enormous interest among the researchers because of its
potential efficiency in solving many optimization problems and real-world
applications. The LCA has ... | computer science |
20,493 | Coalition Formability Semantics with Conflict-Eliminable Sets of
Arguments | cs.AI | We consider abstract-argumentation-theoretic coalition formability in this
work. Taking a model from political alliance among political parties, we will
contemplate profitability, and then formability, of a coalition. As is commonly
understood, a group forms a coalition with another group for a greater good,
the goodne... | computer science |
20,494 | A heuristic algorithm for a single vehicle static bike sharing
rebalancing problem | cs.AI | The static bike rebalancing problem (SBRP) concerns the task of repositioning
bikes among stations in self-service bike-sharing systems. This problem can be
seen as a variant of the one-commodity pickup and delivery vehicle routing
problem, where multiple visits are allowed to be performed at each station,
i.e., the de... | computer science |
20,495 | A Step from Probabilistic Programming to Cognitive Architectures | cs.AI | Probabilistic programming is considered as a framework, in which basic
components of cognitive architectures can be represented in unified and elegant
fashion. At the same time, necessity of adopting some component of cognitive
architectures for extending capabilities of probabilistic programming languages
is pointed o... | computer science |
20,496 | ODE - Augmented Training Improves Anomaly Detection in Sensor Data from
Machines | cs.AI | Machines of all kinds from vehicles to industrial equipment are increasingly
instrumented with hundreds of sensors. Using such data to detect anomalous
behaviour is critical for safety and efficient maintenance. However, anomalies
occur rarely and with great variety in such systems, so there is often
insufficient anoma... | computer science |
20,497 | Brain Emotional Learning-Based Prediction Model (For Long-Term Chaotic
Prediction Applications) | cs.AI | This study suggests a new prediction model for chaotic time series inspired
by the brain emotional learning of mammals. We describe the structure and
function of this model, which is referred to as BELPM (Brain Emotional
Learning-Based Prediction Model). Structurally, the model mimics the connection
between the regions... | computer science |
20,498 | Belief Merging by Source Reliability Assessment | cs.AI | Merging beliefs requires the plausibility of the sources of the information
to be merged. They are typically assumed equally reliable in lack of hints
indicating otherwise; yet, a recent line of research spun from the idea of
deriving this information from the revision process itself. In particular, the
history of prev... | computer science |
20,499 | Asymmetric Move Selection Strategies in Monte-Carlo Tree Search:
Minimizing the Simple Regret at Max Nodes | cs.AI | The combination of multi-armed bandit (MAB) algorithms with Monte-Carlo tree
search (MCTS) has made a significant impact in various research fields. The UCT
algorithm, which combines the UCB bandit algorithm with MCTS, is a good example
of the success of this combination. The recent breakthrough made by AlphaGo,
which ... | computer science |
20,500 | Unethical Research: How to Create a Malevolent Artificial Intelligence | cs.AI | Cybersecurity research involves publishing papers about malicious exploits as
much as publishing information on how to design tools to protect
cyber-infrastructure. It is this information exchange between ethical hackers
and security experts, which results in a well-balanced cyber-ecosystem. In the
blooming domain of A... | computer science |
20,501 | Function-Described Graphs for Structural Pattern Recognition | cs.AI | We present in this article the model Function-described graph (FDG), which is
a type of compact representation of a set of attributed graphs (AGs) that
borrow from Random Graphs the capability of probabilistic modelling of
structural and attribute information. We define the FDGs, their features and
two distance measure... | computer science |
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