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20,802 | Sampling Variations of Lead Sheets | cs.AI | Machine-learning techniques have been recently used with spectacular results
to generate artefacts such as music or text. However, these techniques are
still unable to capture and generate artefacts that are convincingly
structured. In this paper we present an approach to generate structured musical
sequences. We intro... | computer science |
20,803 | SLIM: Semi-Lazy Inference Mechanism for Plan Recognition | cs.AI | Plan Recognition algorithms require to recognize a complete hierarchy
explaining the agent's actions and goals. While the output of such algorithms
is informative to the recognizer, the cost of its calculation is high in
run-time, space, and completeness. Moreover, performing plan recognition online
requires the observ... | computer science |
20,804 | Sequential Plan Recognition | cs.AI | Plan recognition algorithms infer agents' plans from their observed actions.
Due to imperfect knowledge about the agent's behavior and the environment, it
is often the case that there are multiple hypotheses about an agent's plans
that are consistent with the observations, though only one of these hypotheses
is correct... | computer science |
20,805 | FeUdal Networks for Hierarchical Reinforcement Learning | cs.AI | We introduce FeUdal Networks (FuNs): a novel architecture for hierarchical
reinforcement learning. Our approach is inspired by the feudal reinforcement
learning proposal of Dayan and Hinton, and gains power and efficacy by
decoupling end-to-end learning across multiple levels -- allowing it to utilise
different resolut... | computer science |
20,806 | Count-Based Exploration with Neural Density Models | cs.AI | Bellemare et al. (2016) introduced the notion of a pseudo-count, derived from
a density model, to generalize count-based exploration to non-tabular
reinforcement learning. This pseudo-count was used to generate an exploration
bonus for a DQN agent and combined with a mixed Monte Carlo update was
sufficient to achieve s... | computer science |
20,807 | Generalised Discount Functions applied to a Monte-Carlo AImu
Implementation | cs.AI | In recent years, work has been done to develop the theory of General
Reinforcement Learning (GRL). However, there are few examples demonstrating
these results in a concrete way. In particular, there are no examples
demonstrating the known results regarding gener- alised discounting. We have
added to the GRL simulation ... | computer science |
20,808 | Approximate Muscle Guided Beam Search for Three-Index Assignment Problem | cs.AI | As a well-known NP-hard problem, the Three-Index Assignment Problem (AP3) has
attracted lots of research efforts for developing heuristics. However, existing
heuristics either obtain less competitive solutions or consume too much time.
In this paper, a new heuristic named Approximate Muscle guided Beam Search
(AMBS) is... | computer science |
20,809 | A proposal for ethically traceable artificial intelligence | cs.AI | Although the problem of a critique of robotic behavior in near-unanimous
agreement to human norms seems intractable, a starting point of such an
ambition is a framework of the collection of knowledge a priori and experience
a posteriori categorized as a set of synthetical judgments available to the
intelligence, transl... | computer science |
20,810 | Exchangeable choice functions | cs.AI | We investigate how to model exchangeability with choice functions.
Exchangeability is a structural assessment on a sequence of uncertain
variables. We show how such assessments are a special indifference assessment,
and how that leads to a counterpart of de Finetti's Representation Theorem,
both in a finite and a count... | computer science |
20,811 | Evidential supplier selection based on interval data fusion | cs.AI | Supplier selection is a typical multi-criteria decision making (MCDM) problem
and lots of uncertain information exist inevitably. To address this issue, a
new method was proposed based on interval data fusion. Our method follows the
original way to generate classical basic probability assignment(BPA) determined
by the ... | computer science |
20,812 | Functions that Emerge through End-to-End Reinforcement Learning - The
Direction for Artificial General Intelligence - | cs.AI | Recently, triggered by the impressive results in TV-games or game of Go by
Google DeepMind, end-to-end reinforcement learning (RL) is collecting
attentions. Although little is known, the author's group has propounded this
framework for around 20 years and already has shown various functions that
emerge in a neural netw... | computer science |
20,813 | Using Options and Covariance Testing for Long Horizon Off-Policy Policy
Evaluation | cs.AI | Evaluating a policy by deploying it in the real world can be risky and
costly. Off-policy policy evaluation (OPE) algorithms use historical data
collected from running a previous policy to evaluate a new policy, which
provides a means for evaluating a policy without requiring it to ever be
deployed. Importance sampling... | computer science |
20,814 | Communications that Emerge through Reinforcement Learning Using a
(Recurrent) Neural Network | cs.AI | Communication is not only an action of choosing a signal, but needs to
consider the context and sensor signals. It also needs to decide what
information is communicated and how it is represented in or understood from
signals. Therefore, communication should be realized comprehensively together
with its purpose and othe... | computer science |
20,815 | On Quantum Decision Trees | cs.AI | Quantum decision systems are being increasingly considered for use in
artificial intelligence applications. Classical and quantum nodes can be
distinguished based on certain correlations in their states. This paper
investigates some properties of the states obtained in a decision tree
structure. How these correlations ... | computer science |
20,816 | Front-to-End Bidirectional Heuristic Search with Near-Optimal Node
Expansions | cs.AI | It is well-known that any admissible unidirectional heuristic search
algorithm must expand all states whose $f$-value is smaller than the optimal
solution cost when using a consistent heuristic. Such states are called "surely
expanded" (s.e.). A recent study characterized s.e. pairs of states for
bidirectional search w... | computer science |
20,817 | Axioms in Model-based Planners | cs.AI | Axioms can be used to model derived predicates in domain- independent
planning models. Formulating models which use axioms can sometimes result in
problems with much smaller search spaces and shorter plans than the original
model. Previous work on axiom-aware planners focused solely on state- space
search planners. We ... | computer science |
20,818 | Micro-Objective Learning : Accelerating Deep Reinforcement Learning
through the Discovery of Continuous Subgoals | cs.AI | Recently, reinforcement learning has been successfully applied to the logical
game of Go, various Atari games, and even a 3D game, Labyrinth, though it
continues to have problems in sparse reward settings. It is difficult to
explore, but also difficult to exploit, a small number of successes when
learning policy. To so... | computer science |
20,819 | BetaRun Soccer Simulation League Team: Variety, Complexity, and Learning | cs.AI | RoboCup offers a set of benchmark problems for Artificial Intelligence in
form of official world championships since 1997. The most tactical advanced and
richest in terms of behavioural complexity of these is the 2D Soccer Simulation
League, a simulated robotic soccer competition. BetaRun is a new attempt
combining bot... | computer science |
20,820 | Any-Angle Pathfinding for Multiple Agents Based on SIPP Algorithm | cs.AI | The problem of finding conflict-free trajectories for multiple agents of
identical circular shape, operating in shared 2D workspace, is addressed in the
paper and decoupled, e.g., prioritized, approach is used to solve this problem.
Agents' workspace is tessellated into the square grid on which any-angle moves
are allo... | computer science |
20,821 | Numerical Integration and Dynamic Discretization in Heuristic Search
Planning over Hybrid Domains | cs.AI | In this paper we look into the problem of planning over hybrid domains, where
change can be both discrete and instantaneous, or continuous over time. In
addition, it is required that each state on the trajectory induced by the
execution of plans complies with a given set of global constraints. We approach
the computati... | computer science |
20,822 | Toward a Formal Model of Cognitive Synergy | cs.AI | "Cognitive synergy" refers to a dynamic in which multiple cognitive
processes, cooperating to control the same cognitive system, assist each other
in overcoming bottlenecks encountered during their internal processing.
Cognitive synergy has been posited as a key feature of real-world general
intelligence, and has been ... | computer science |
20,823 | Symbol Grounding via Chaining of Morphisms | cs.AI | A new model of symbol grounding is presented, in which the structures of
natural language, logical semantics, perception and action are represented
categorically, and symbol grounding is modeled via the composition of morphisms
between the relevant categories. This model gives conceptual insight into the
fundamentally ... | computer science |
20,824 | Cost-Based Intuitionist Probabilities on Spaces of Graphs, Hypergraphs
and Theorems | cs.AI | A novel partial order is defined on the space of digraphs or hypergraphs,
based on assessing the cost of producing a graph via a sequence of elementary
transformations. Leveraging work by Knuth and Skilling on the foundations of
inference, and the structure of Heyting algebras on graph space, this partial
order is used... | computer science |
20,825 | Minimizing Maximum Regret in Commitment Constrained Sequential Decision
Making | cs.AI | In cooperative multiagent planning, it can often be beneficial for an agent
to make commitments about aspects of its behavior to others, allowing them in
turn to plan their own behaviors without taking the agent's detailed behavior
into account. Extending previous work in the Bayesian setting, we consider
instead a wor... | computer science |
20,826 | Towards Moral Autonomous Systems | cs.AI | Both the ethics of autonomous systems and the problems of their technical
implementation have by now been studied in some detail. Less attention has been
given to the areas in which these two separate concerns meet. This paper,
written by both philosophers and engineers of autonomous systems, addresses a
number of issu... | computer science |
20,827 | Exploring the Combination Rules of D Numbers From a Perspective of
Conflict Redistribution | cs.AI | Dempster-Shafer theory of evidence is widely applied to uncertainty modelling
and knowledge reasoning because of its advantages in dealing with uncertain
information. But some conditions or requirements, such as exclusiveness
hypothesis and completeness constraint, limit the development and application
of that theory t... | computer science |
20,828 | Syntax-Preserving Belief Change Operators for Logic Programs | cs.AI | Recent methods have adapted the well-established AGM and belief base
frameworks for belief change to cover belief revision in logic programs. In
this study here, we present two new sets of belief change operators for logic
programs. They focus on preserving the explicit relationships expressed in the
rules of a program... | computer science |
20,829 | Fuzzy Rankings: Properties and Applications | cs.AI | In practice, a ranking of objects with respect to given set of criteria is of
considerable importance. However, due to lack of knowledge, information of time
pressure, decision makers might not be able to provide a (crisp) ranking of
objects from the top to the bottom. Instead, some objects might be ranked
equally, or ... | computer science |
20,830 | On Inconsistency Indices and Inconsistency Axioms in Pairwise
Comparisons | cs.AI | Pairwise comparisons are an important tool of modern (multiple criteria)
decision making. Since human judgments are often inconsistent, many studies
focused on the ways how to express and measure this inconsistency, and several
inconsistency indices were proposed as an alternative to Saaty inconsistency
index and incon... | computer science |
20,831 | Finite Sample Analysis of Two-Timescale Stochastic Approximation with
Applications to Reinforcement Learning | cs.AI | Two-timescale Stochastic Approximation (SA) algorithms are widely used in
Reinforcement Learning (RL). Their iterates have two parts that are updated
using distinct stepsizes. In this work, we develop a novel recipe for their
finite sample analysis. Using this, we provide a concentration bound, which is
the first such ... | computer science |
20,832 | ParaGraphE: A Library for Parallel Knowledge Graph Embedding | cs.AI | Knowledge graph embedding aims at translating the knowledge graph into
numerical representations by transforming the entities and relations into
continuous low-dimensional vectors. Recently, many methods [1, 5, 3, 2, 6] have
been proposed to deal with this problem, but existing single-thread
implementations of them are... | computer science |
20,833 | Approximation Complexity of Maximum A Posteriori Inference in
Sum-Product Networks | cs.AI | We discuss the computational complexity of approximating maximum a posteriori
inference in sum-product networks. We first show NP-hardness in trees of height
two by a reduction from maximum independent set; this implies
non-approximability within a sublinear factor. We show that this is a tight
bound, as we can find an... | computer science |
20,834 | Cooperating with Machines | cs.AI | Since Alan Turing envisioned Artificial Intelligence (AI) [1], a major
driving force behind technical progress has been competition with human
cognition. Historical milestones have been frequently associated with computers
matching or outperforming humans in difficult cognitive tasks (e.g. face
recognition [2], persona... | computer science |
20,835 | Evolving Game Skill-Depth using General Video Game AI Agents | cs.AI | Most games have, or can be generalised to have, a number of parameters that
may be varied in order to provide instances of games that lead to very
different player experiences. The space of possible parameter settings can be
seen as a search space, and we can therefore use a Random Mutation Hill
Climbing algorithm or o... | computer science |
20,836 | Solving the Goddard problem by an influence diagram | cs.AI | Influence diagrams are a decision-theoretic extension of probabilistic
graphical models. In this paper we show how they can be used to solve the
Goddard problem. We present results of numerical experiments with this problem
and compare the solutions provided by influence diagrams with the optimal
solution. | computer science |
20,837 | Goal Conflict in Designing an Autonomous Artificial System | cs.AI | Research on human self-regulation has shown that people hold many goals
simultaneously and have complex self-regulation mechanisms to deal with this
goal conflict. Artificial autonomous systems may also need to find ways to cope
with conflicting goals. Indeed, the intricate interplay among different goals
may be critic... | computer science |
20,838 | Multi-Timescale, Gradient Descent, Temporal Difference Learning with
Linear Options | cs.AI | Deliberating on large or continuous state spaces have been long standing
challenges in reinforcement learning. Temporal Abstraction have somewhat made
this possible, but efficiently planing using temporal abstraction still remains
an issue. Moreover using spatial abstractions to learn policies for various
situations at... | computer science |
20,839 | Evidence Updating for Stream-Processing in Big-Data: Robust Conditioning
in Soft and Hard Fusion Environments | cs.AI | Robust belief revision methods are crucial in streaming data situations for
updating existing knowledge or beliefs with new incoming evidence. Bayes
conditioning is the primary mechanism in use for belief revision in data fusion
systems that use probabilistic inference. However, traditional conditioning
methods face se... | computer science |
20,840 | Artificial Intelligence and Economic Theories | cs.AI | The advent of artificial intelligence has changed many disciplines such as
engineering, social science and economics. Artificial intelligence is a
computational technique which is inspired by natural intelligence such as the
swarming of birds, the working of the brain and the pathfinding of the ants.
These techniques h... | computer science |
20,841 | Foundations for a Probabilistic Event Calculus | cs.AI | We present PEC, an Event Calculus (EC) style action language for reasoning
about probabilistic causal and narrative information. It has an action language
style syntax similar to that of the EC variant Modular-E. Its semantics is
given in terms of possible worlds which constitute possible evolutions of the
domain, and ... | computer science |
20,842 | Distributed Constraint Problems for Utilitarian Agents with Privacy
Concerns, Recast as POMDPs | cs.AI | Privacy has traditionally been a major motivation for distributed problem
solving. Distributed Constraint Satisfaction Problem (DisCSP) as well as
Distributed Constraint Optimization Problem (DCOP) are fundamental models used
to solve various families of distributed problems. Even though several
approaches have been pr... | computer science |
20,843 | Pseudorehearsal in value function approximation | cs.AI | Catastrophic forgetting is of special importance in reinforcement learning,
as the data distribution is generally non-stationary over time. We study and
compare several pseudorehearsal approaches for Q-learning with function
approximation in a pole balancing task. We have found that pseudorehearsal
seems to assist lear... | computer science |
20,844 | RobustFill: Neural Program Learning under Noisy I/O | cs.AI | The problem of automatically generating a computer program from some
specification has been studied since the early days of AI. Recently, two
competing approaches for automatic program learning have received significant
attention: (1) neural program synthesis, where a neural network is conditioned
on input/output (I/O)... | computer science |
20,845 | Diversification-Based Learning in Computing and Optimization | cs.AI | Diversification-Based Learning (DBL) derives from a collection of principles
and methods introduced in the field of metaheuristics that have broad
applications in computing and optimization. We show that the DBL framework goes
significantly beyond that of the more recent Opposition-based learning (OBL)
framework introd... | computer science |
20,846 | Reasoning by Cases in Structured Argumentation | cs.AI | We extend the $ASPIC^+$ framework for structured argumentation so as to allow
applications of the reasoning by cases inference scheme for defeasible
arguments. Given an argument with conclusion `$A$ or $B$', an argument based on
$A$ with conclusion $C$, and an argument based on $B$ with conclusion $C$, we
allow the con... | computer science |
20,847 | Team Formation for Scheduling Educational Material in Massive Online
Classes | cs.AI | Whether teaching in a classroom or a Massive Online Open Course it is crucial
to present the material in a way that benefits the audience as a whole. We
identify two important tasks to solve towards this objective, 1 group students
so that they can maximally benefit from peer interaction and 2 find an optimal
schedule ... | computer science |
20,848 | Learning and inference in knowledge-based probabilistic model for
medical diagnosis | cs.AI | Based on a weighted knowledge graph to represent first-order knowledge and
combining it with a probabilistic model, we propose a methodology for the
creation of a medical knowledge network (MKN) in medical diagnosis. When a set
of symptoms is activated for a specific patient, we can generate a ground
medical knowledge ... | computer science |
20,849 | Mining Best Closed Itemsets for Projection-antimonotonic Constraints in
Polynomial Time | cs.AI | The exponential explosion of the set of patterns is one of the main
challenges in pattern mining. This challenge is approached by introducing a
constraint for pattern selection. One of the first constraints proposed in
pattern mining is support (frequency) of a pattern in a dataset. Frequency is
an anti-monotonic funct... | computer science |
20,850 | Universal Reasoning, Rational Argumentation and Human-Machine
Interaction | cs.AI | Classical higher-order logic, when utilized as a meta-logic in which various
other (classical and non-classical) logics can be shallowly embedded, is well
suited for realising a universal logic reasoning approach. Universal logic
reasoning in turn, as envisioned already by Leibniz, may support the rigorous
formalisatio... | computer science |
20,851 | On Convergence Property of Implicit Self-paced Objective | cs.AI | Self-paced learning (SPL) is a new methodology that simulates the learning
principle of humans/animals to start learning easier aspects of a learning
task, and then gradually take more complex examples into training. This
new-coming learning regime has been empirically substantiated to be effective
in various computer ... | computer science |
20,852 | Spaceprint: a Mobility-based Fingerprinting Scheme for Public Spaces | cs.AI | In this paper, we address the problem of how automated situation-awareness
can be achieved by learning real-world situations from ubiquitously generated
mobility data. Without semantic input about the time and space where situations
take place, this turns out to be a fundamental challenging problem.
Uncertainties also ... | computer science |
20,853 | Efficient Parallel Translating Embedding For Knowledge Graphs | cs.AI | Knowledge graph embedding aims to embed entities and relations of knowledge
graphs into low-dimensional vector spaces. Translating embedding methods regard
relations as the translation from head entities to tail entities, which achieve
the state-of-the-art results among knowledge graph embedding methods. However,
a maj... | computer science |
20,854 | An Empirical Approach for Modeling Fuzzy Geographical Descriptors | cs.AI | We present a novel heuristic approach that defines fuzzy geographical
descriptors using data gathered from a survey with human subjects. The
participants were asked to provide graphical interpretations of the descriptors
`north' and `south' for the Galician region (Spain). Based on these
interpretations, our approach b... | computer science |
20,855 | Comparison of ontology alignment algorithms across single matching task
via the McNemar test | cs.AI | Ontology alignment is widely used to find the correspondences between
different ontologies in diverse fields. After discovering the alignment by
methods, several performance scores are available to evaluate them. The scores
require the produced alignment by a method and the reference alignment
containing the underlying... | computer science |
20,856 | Structured Parallel Programming for Monte Carlo Tree Search | cs.AI | In this paper, we present a new algorithm for parallel Monte Carlo tree
search (MCTS). It is based on the pipeline pattern and allows flexible
management of the control flow of the operations in parallel MCTS. The pipeline
pattern provides for the first structured parallel programming approach to
MCTS. Moreover, we pro... | computer science |
20,857 | A History of Metaheuristics | cs.AI | This chapter describes the history of metaheuristics in five distinct
periods, starting long before the first use of the term and ending a long time
in the future. | computer science |
20,858 | A simulated annealing approach to optimal storing in a multi-level
warehouse | cs.AI | We propose a simulated annealing algorithm specifically tailored to optimise
total retrieval times in a multi-level warehouse under complex pre-batched
picking constraints. Experiments on real data from a picker-to-parts order
picking process in the warehouse of a European manufacturer show that optimal
storage assignm... | computer science |
20,859 | Finite Sample Analyses for TD(0) with Function Approximation | cs.AI | TD(0) is one of the most commonly used algorithms in reinforcement learning.
Despite this, there is no existing finite sample analysis for TD(0) with
function approximation, even for the linear case. Our work is the first to
provide such results. Existing convergence rates for Temporal Difference (TD)
methods apply onl... | computer science |
20,860 | Transferrable Plausibility Model - A Probabilistic Interpretation of
Mathematical Theory of Evidence | cs.AI | This paper suggests a new interpretation of the Dempster-Shafer theory in
terms of probabilistic interpretation of plausibility. A new rule of
combination of independent evidence is shown and its preservation of
interpretation is demonstrated. | computer science |
20,861 | The quality of priority ratios estimation in relation to a selected
prioritization procedure and consistency measure for a Pairwise Comparison
Matrix | cs.AI | An overview of current debates and contemporary research devoted to the
modeling of decision making processes and their facilitation directs attention
to the Analytic Hierarchy Process (AHP). At the core of the AHP are various
prioritization procedures (PPs) and consistency measures (CMs) for a Pairwise
Comparison Matr... | computer science |
20,862 | Basic Formal Properties of A Relational Model of The Mathematical Theory
of Evidence | cs.AI | The paper presents a novel view of the Dempster-Shafer belief function as a
measure of diversity in relational data bases. It is demonstrated that under
the interpretation The Dempster rule of evidence combination corresponds to the
join operator of the relational database theory. This rough-set based
interpretation is... | computer science |
20,863 | Matching Media Contents with User Profiles by means of the
Dempster-Shafer Theory | cs.AI | The media industry is increasingly personalizing the offering of contents in
attempt to better target the audience. This requires to analyze the
relationships that goes established between users and content they enjoy,
looking at one side to the content characteristics and on the other to the user
profile, in order to ... | computer science |
20,864 | Beliefs and Probability in Bacchus' l.p. Logic: A~3-Valued Logic
Solution to Apparent Counter-intuition | cs.AI | Fundamental discrepancy between first order logic and statistical inference
(global versus local properties of universe) is shown to be the obstacle for
integration of logic and probability in L.p. logic of Bacchus. To overcome the
counterintuitiveness of L.p. behaviour, a 3-valued logic is proposed. | computer science |
20,865 | Next Generation Business Intelligence and Analytics: A Survey | cs.AI | Business Intelligence and Analytics (BI&A) is the process of extracting and
predicting business-critical insights from data. Traditional BI focused on data
collection, extraction, and organization to enable efficient query processing
for deriving insights from historical data. With the rise of big data and cloud
comput... | computer science |
20,866 | CASP Solutions for Planning in Hybrid Domains | cs.AI | CASP is an extension of ASP that allows for numerical constraints to be added
in the rules. PDDL+ is an extension of the PDDL standard language of automated
planning for modeling mixed discrete-continuous dynamics.
In this paper, we present CASP solutions for dealing with PDDL+ problems,
i.e., encoding from PDDL+ to ... | computer science |
20,867 | Finding Modes by Probabilistic Hypergraphs Shifting | cs.AI | In this paper, we develop a novel paradigm, namely hypergraph shift, to find
robust graph modes by probabilistic voting strategy, which are semantically
sound besides the self-cohesiveness requirement in forming graph modes. Unlike
the existing techniques to seek graph modes by shifting vertices based on
pair-wise edge... | computer science |
20,868 | Beliefs in Markov Trees - From Local Computations to Local Valuation | cs.AI | This paper is devoted to expressiveness of hypergraphs for which uncertainty
propagation by local computations via Shenoy/Shafer method applies. It is
demonstrated that for this propagation method for a given joint belief
distribution no valuation of hyperedges of a hypergraph may provide with
simpler hypergraph struct... | computer science |
20,869 | Dempster-Shafer Belief Function - A New Interpretation | cs.AI | We develop our interpretation of the joint belief distribution and of
evidential updating that matches the following basic requirements:
* there must exist an efficient method for reasoning within this framework
* there must exist a clear correspondence between the contents of the
knowledge base and the real world
... | computer science |
20,870 | Environment-Independent Task Specifications via GLTL | cs.AI | We propose a new task-specification language for Markov decision processes
that is designed to be an improvement over reward functions by being
environment independent. The language is a variant of Linear Temporal Logic
(LTL) that is extended to probabilistic specifications in a way that permits
approximations to be le... | computer science |
20,871 | The Reactor: A Sample-Efficient Actor-Critic Architecture | cs.AI | In this work we present a new reinforcement learning agent, called Reactor
(for Retrace-actor), based on an off-policy multi-step return actor-critic
architecture. The agent uses a deep recurrent neural network for function
approximation. The network outputs a target policy {\pi} (the actor), an
action-value Q-function... | computer science |
20,872 | FML-based Prediction Agent and Its Application to Game of Go | cs.AI | In this paper, we present a robotic prediction agent including a darkforest
Go engine, a fuzzy markup language (FML) assessment engine, an FML-based
decision support engine, and a robot engine for game of Go application. The
knowledge base and rule base of FML assessment engine are constructed by
referring the informat... | computer science |
20,873 | Approximating the Backbone in the Weighted Maximum Satisfiability
Problem | cs.AI | The weighted Maximum Satisfiability problem (weighted MAX-SAT) is a NP-hard
problem with numerous applications arising in artificial intelligence. As an
efficient tool for heuristic design, the backbone has been applied to
heuristics design for many NP-hard problems. In this paper, we investigated the
computational com... | computer science |
20,874 | Pseudorehearsal in actor-critic agents | cs.AI | Catastrophic forgetting has a serious impact in reinforcement learning, as
the data distribution is generally sparse and non-stationary over time. The
purpose of this study is to investigate whether pseudorehearsal can increase
performance of an actor-critic agent with neural-network based policy selection
and function... | computer science |
20,875 | Probabilistic programs for inferring the goals of autonomous agents | cs.AI | Intelligent systems sometimes need to infer the probable goals of people,
cars, and robots, based on partial observations of their motion. This paper
introduces a class of probabilistic programs for formulating and solving these
problems. The formulation uses randomized path planning algorithms as the basis
for probabi... | computer science |
20,876 | Anomaly detection and motif discovery in symbolic representations of
time series | cs.AI | The advent of the Big Data hype and the consistent recollection of event logs
and real-time data from sensors, monitoring software and machine configuration
has generated a huge amount of time-varying data in about every sector of the
industry. Rule-based processing of such data has ceased to be relevant in many
scenar... | computer science |
20,877 | Synergy of all-purpose static solver and temporal reasoning tools in
dynamic integrated expert systems | cs.AI | The paper discusses scientific and technological problems of dynamic
integrated expert systems development. Extensions of problem-oriented
methodology for dynamic integrated expert systems development are considered.
Attention is paid to the temporal knowledge representation and processing. | computer science |
20,878 | Beating Atari with Natural Language Guided Reinforcement Learning | cs.AI | We introduce the first deep reinforcement learning agent that learns to beat
Atari games with the aid of natural language instructions. The agent uses a
multimodal embedding between environment observations and natural language to
self-monitor progress through a list of English instructions, granting itself
reward for ... | computer science |
20,879 | Using Contexts and Constraints for Improved Geotagging of Human
Trafficking Webpages | cs.AI | Extracting geographical tags from webpages is a well-motivated application in
many domains. In illicit domains with unusual language models, like human
trafficking, extracting geotags with both high precision and recall is a
challenging problem. In this paper, we describe a geotag extraction framework
in which context,... | computer science |
20,880 | The Dependent Doors Problem: An Investigation into Sequential Decisions
without Feedback | cs.AI | We introduce the dependent doors problem as an abstraction for situations in
which one must perform a sequence of possibly dependent decisions, without
receiving feedback information on the effectiveness of previously made actions.
Informally, the problem considers a set of $d$ doors that are initially closed,
and the ... | computer science |
20,881 | A Reinforcement Learning Approach to Weaning of Mechanical Ventilation
in Intensive Care Units | cs.AI | The management of invasive mechanical ventilation, and the regulation of
sedation and analgesia during ventilation, constitutes a major part of the care
of patients admitted to intensive care units. Both prolonged dependence on
mechanical ventilation and premature extubation are associated with increased
risk of compli... | computer science |
20,882 | Accurately and Efficiently Interpreting Human-Robot Instructions of
Varying Granularities | cs.AI | Humans can ground natural language commands to tasks at both abstract and
fine-grained levels of specificity. For instance, a human forklift operator can
be instructed to perform a high-level action, like "grab a pallet" or a
lowlevel action like "tilt back a little bit." While robots are also capable of
grounding lang... | computer science |
20,883 | A hybrid spatial data mining approach based on fuzzy topological
relations and MOSES evolutionary algorithm | cs.AI | Making high-quality decisions in strategic spatial planning is heavily
dependent on extracting knowledge from vast amounts of data. Although many
decision-making problems like developing urban areas require such perception
and reasoning, existing methods in this field usually neglect the deep
knowledge mined from geogr... | computer science |
20,884 | General Video Game AI: Learning from Screen Capture | cs.AI | General Video Game Artificial Intelligence is a general game playing
framework for Artificial General Intelligence research in the video-games
domain. In this paper, we propose for the first time a screen capture learning
agent for General Video Game AI framework. A Deep Q-Network algorithm was
applied and improved to ... | computer science |
20,885 | Evaluating and Modelling Hanabi-Playing Agents | cs.AI | Agent modelling involves considering how other agents will behave, in order
to influence your own actions. In this paper, we explore the use of agent
modelling in the hidden-information, collaborative card game Hanabi. We
implement a number of rule-based agents, both from the literature and of our
own devising, in addi... | computer science |
20,886 | Analysis of Vanilla Rolling Horizon Evolution Parameters in General
Video Game Playing | cs.AI | Monte Carlo Tree Search techniques have generally dominated General Video
Game Playing, but recent research has started looking at Evolutionary
Algorithms and their potential at matching Tree Search level of play or even
outperforming these methods. Online or Rolling Horizon Evolution is one of the
options available to... | computer science |
20,887 | Stochastic Constraint Programming as Reinforcement Learning | cs.AI | Stochastic Constraint Programming (SCP) is an extension of Constraint
Programming (CP) used for modelling and solving problems involving constraints
and uncertainty. SCP inherits excellent modelling abilities and filtering
algorithms from CP, but so far it has not been applied to large problems.
Reinforcement Learning ... | computer science |
20,888 | Learning from Ontology Streams with Semantic Concept Drift | cs.AI | Data stream learning has been largely studied for extracting knowledge
structures from continuous and rapid data records. In the semantic Web, data is
interpreted in ontologies and its ordered sequence is represented as an
ontology stream. Our work exploits the semantics of such streams to tackle the
problem of concept... | computer science |
20,889 | Molecular De Novo Design through Deep Reinforcement Learning | cs.AI | This work introduces a method to tune a sequence-based generative model for
molecular de novo design that through augmented episodic likelihood can learn
to generate structures with certain specified desirable properties. We
demonstrate how this model can execute a range of tasks such as generating
analogues to a query... | computer science |
20,890 | Reinforcement Learning-based Thermal Comfort Control for Vehicle Cabins | cs.AI | Vehicle climate control systems aim to keep passengers thermally comfortable.
However, current systems control temperature rather than thermal comfort and
tend to be energy hungry, which is of particular concern when considering
electric vehicles. This paper poses energy-efficient vehicle comfort control as
a Markov De... | computer science |
20,891 | Structured Production System (extended abstract) | cs.AI | In this extended abstract, we propose Structured Production Systems (SPS),
which extend traditional production systems with well-formed syntactic
structures. Due to the richness of structures, structured production systems
significantly enhance the expressive power as well as the flexibility of
production systems, for ... | computer science |
20,892 | A Popperian Falsification of AI - Lighthill's Argument Defended | cs.AI | The area of computation called artificial intelligence (AI) is falsified by
describing a previous 1972 falsification of AI by British applied mathematician
James Lighthill. It is explained how Lighthill's arguments continue to apply to
current AI. It is argued that AI should use the Popperian scientific method in
which... | computer science |
20,893 | The MacGyver Test - A Framework for Evaluating Machine Resourcefulness
and Creative Problem Solving | cs.AI | Current measures of machine intelligence are either difficult to evaluate or
lack the ability to test a robot's problem-solving capacity in open worlds. We
propose a novel evaluation framework based on the formal notion of MacGyver
Test which provides a practical way for assessing the resilience and
resourcefulness of ... | computer science |
20,894 | Consensus measure of rankings | cs.AI | A ranking is an ordered sequence of items, in which an item with higher
ranking score is more preferred than the items with lower ranking scores. In
many information systems, rankings are widely used to represent the preferences
over a set of items or candidates. The consensus measure of rankings is the
problem of how ... | computer science |
20,895 | Intelligent Personal Assistant with Knowledge Navigation | cs.AI | An Intelligent Personal Agent (IPA) is an agent that has the purpose of
helping the user to gain information through reliable resources with the help
of knowledge navigation techniques and saving time to search the best content.
The agent is also responsible for responding to the chat-based queries with the
help of Con... | computer science |
20,896 | Classical Planning in Deep Latent Space: Bridging the
Subsymbolic-Symbolic Boundary | cs.AI | Current domain-independent, classical planners require symbolic models of the
problem domain and instance as input, resulting in a knowledge acquisition
bottleneck. Meanwhile, although deep learning has achieved significant success
in many fields, the knowledge is encoded in a subsymbolic representation which
is incomp... | computer science |
20,897 | A Partitioning Algorithm for Detecting Eventuality Coincidence in
Temporal Double recurrence | cs.AI | A logical theory of regular double or multiple recurrence of eventualities,
which are regular patterns of occurrences that are repeated, in time, has been
developed within the context of temporal reasoning that enabled reasoning about
the problem of coincidence. i.e. if two complex eventualities, or eventuality
sequenc... | computer science |
20,898 | Defense semantics of argumentation: encoding reasons for accepting
arguments | cs.AI | In this paper we show how the defense relation among abstract arguments can
be used to encode the reasons for accepting arguments. After introducing a
novel notion of defenses and defense graphs, we propose a defense semantics
together with a new notion of defense equivalence of argument graphs, and
compare defense equ... | computer science |
20,899 | The Problem of Coincidence in A Theory of Temporal Multiple Recurrence | cs.AI | Logical theories have been developed which have allowed temporal reasoning
about eventualities (a la Galton) such as states, processes, actions, events,
processes and complex eventualities such as sequences and recurrences of other
eventualities. This paper presents the problem of coincidence within the
framework of a ... | computer science |
20,900 | An improved Ant Colony System for the Sequential Ordering Problem | cs.AI | It is not rare that the performance of one metaheuristic algorithm can be
improved by incorporating ideas taken from another. In this article we present
how Simulated Annealing (SA) can be used to improve the efficiency of the Ant
Colony System (ACS) and Enhanced ACS when solving the Sequential Ordering
Problem (SOP). ... | computer science |
20,901 | The N-Tuple Bandit Evolutionary Algorithm for Automatic Game Improvement | cs.AI | This paper describes a new evolutionary algorithm that is especially well
suited to AI-Assisted Game Design. The approach adopted in this paper is to use
observations of AI agents playing the game to estimate the game's quality. Some
of best agents for this purpose are General Video Game AI agents, since they
can be de... | computer science |
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