AI 2015: Advances in Artificial Intelligence

Name: AI 2015: Advances in Artificial Intelligence | 28th Australasian Joint Conference, Canberra, ACT, Australia, November 30 -- December 4, 2015, Proceedings
Brand: Springer
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28th Australasian Joint Conference, Canberra, ACT, Australia, November 30 -- December 4, 2015, Proceedings

Bernhard Pfahringer Jochen Renz(Herausgeber*in)

Springer (Verlag)

Erschienen am 21. November 2015

XVII, 652 Seiten

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978-3-319-26350-2 (ISBN)

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Inhalt

Intro
Preface
Organization
Contents
Exploiting the Beta Distribution-Based Reputation Model in Recommender System
Abstract
1 Introduction
2 Related Work
3 The Beta Distribution-Based Reputation Model
3.1 Normal Distribution-Based Reputation Model
3.2 Weighting Based on the Standard Beta Distribution
3.3 Reputation Score Generation
3.4 The Beta Distribution Shapes
4 Incorporating Reputation in Recommender System
4.1 The Weighted Borda-Count Method
4.2 Using Personalized Item Reputation
5 Experiment
5.1 Dataset
5.2 Experiment Settings
5.3 Results and Discussion
6 Conclusions
References
A Heuristic Search Approach to Find Contrail Avoidance Flight Routes
Abstract
1 Introduction
2 Background
3 Methodology
3.1 Airspace Model
3.2 Atmospheric Model
3.3 Persistent Contrail Model
3.4 Flight Route Model
3.5 Integration of Contrail, Flight Route, Atmosphere and Airspace
3.6 Algorithm Design
4 Experiment Design
5 Results
6 Analysis and Future Work
References
Temporal Conjunctive Queries in Expressive Description Logics with Transitive Roles
1 Introduction
2 Preliminaries
3 Atemporal Queries in SHIQ, SHOQ, and SHOI
4 Combined Complexity of TCQ Entailment
5 Data Complexity Without Rigid Roles
6 Conclusions
References
Scaling up Multi-island Competitive Cooperative Coevolution for Real Parameter Global Optimisation
1 Introduction
2 Multi-island Competitive Cooperative Coevolution
2.1 Initialization
2.2 Cooperative Coevolution
2.3 Competition
2.4 Collaboration: Inter-island Interaction and Solution Migration
3 Simulation and Analyses
3.1 Benchmark Problems and Parameter Settings
3.2 Results and Analysis
3.3 Performance Analysis of MICCC as the Number of Islands Increase
3.4 Island Competition Analysis over the Evolutionary Process
4 Conclusion
References
An Evolutionary Algorithm with Classifier Guided Constraint Evaluation Strategy for Computationally Expensive Optimization Problems
1 Background
2 Proposed Approach
2.1 Test Function
3 Numerical Experiments
4 Results and Discussion
4.1 Performance on Problems
5 Summary and Conclusions
References
Cost to Evaluate Versus Cost to Learn? Performance of Selective Evaluation Strategies in Multiobjective Optimization
1 Background
2 Performance of Various Classifier Models
3 Experimental Results
3.1 Illustrative Example: DTLZ1
3.2 Performance on DTLZ Problem Suite
4 Summary and Conclusions
References
A Propositional Plausible Logic
1 Introduction
2 PPL: A Propositional Plausible Logic
3 The Ambiguity Puzzle
4 Theorems About Propositional Plausible Logic
5 Conclusion
References
Monte Carlo Analysis of a Puzzle Game
1 Introduction
1.1 BoxOff
1.2 Game Design Goals
2 Complexity
2.1 Challenge Space Complexity
2.2 Game Tree Complexity
2.3 State Space Complexity
2.4 Computational Complexity
3 Experiments
3.1 2D Case
3.2 1D Case
3.3 3D Case
4 Tension
5 Conclusion
References
Tracking Drift Severity in Data Streams
1 Introduction
2 Background
3 Related Work
4 MagSeed Drift Detector
5 Experiments
5.1 Experimental Setup
5.2 Drift Detection
5.3 Warning Detection and Severity Measure
5.4 Performance on Real World Data
6 Conclusions
References
Probabilistic Belief Contraction: Considerations on Epistemic Entrenchment, Probability Mixtures and KL Divergence
1 Introduction
2 Background
3 What Is ?
3.1 Two Views on
4 The Kullback-Leibler Divergence
5 Conclusion
References
DMAPP: A Distributed Multi-agent Path Planning Algorithm
1 Introduction
2 Related Work
3 A Distributed Multi-agent Path Planning Algorithm
3.1 Path Planning
3.2 Priority Decision-Making
3.3 Plan Restructuring
4 Implementation
4.1 Warehouse Domain
5 Conclusions
References
Graph-Based Collaborative Filtering Using Rating Nodes: A Solution to the High Ratings/Low Ratings P ...
Abstract
1 Introduction
2 Graph-Based Recommender Models
2.1 The High Ratings/Low Ratings Problem
3 Rating Node Representation
3.1 High Ratings/Low Ratings Revisited
3.2 Recommendation Value
3.3 Additional Comments
4 Experiments
4.1 Correlation-Based Evaluation
4.2 Top-K Evaluation
5 Conclusion
References
A Comparative Study on Vector Similarity Methods for Offer Generation in Multi-attribute Negotiation
Abstract
1 Introduction
2 Negotiation Settings
3 Vector Similarities for Offer Generation
4 Experiment and Results
4.1 Negotiation Domain
4.2 Negotiation Outcome Evaluation
4.3 Results and Discussion
5 Conclusion
References
Analytical Results on the BFS vs. DFS Algorithm Selection Problem. Part I: Tree Search
1 Introduction
2 Preliminaries
3 Complete Binary Tree with a Single Goal Level
4 Complete Binary Tree with Multiple Goal Levels
5 Experimental Verification
6 Conclusions and Outlook
References
Analytical Results on the BFS vs. DFS Algorithm Selection Problem: Part II: Graph Search
1 Introduction
2 Preliminaries
3 Colliding Branches
3.1 DFS Analysis
3.2 BFS Analysis
4 Grammar Problems
4.1 Binary Grammar
4.2 Full Grammar
5 Experimental Verification
6 Discussion
References
Region-Growing Planar Segmentation for Robot Action Planning
1 Introduction
2 Background Work
3 Experimental Evaluation
3.1 Dataset
3.2 Parameters
3.3 Data Preparation
3.4 Evaluating SP
3.5 Evaluating SNP
3.6 Comparing SNP and Our Method
4 Conclusion
References
A Differentially Private Random Decision Forest Using Reliable Signal-to-Noise Ratios
1 Introduction
1.1 Problem Statement
1.2 Our Contributions
2 Previous Work
2.1 Differential Privacy
2.2 Previous Differentially Private Decision Trees
3 Signal-to-Noise Ratio
3.1 Signal Averaging
4 Our Differentially Private Random Decision Forest
4.1 Overview of Our Algorithm, DP-RF
4.2 Querying the Leafs of a Tree
4.3 Building a Random Tree
4.4 Defining the Number of Trees
4.5 Pruning to a Reliable Depth
4.6 Finding the Most Confident Prediction in Each Rule
4.7 Voting
5 Experiments
6 Conclusion
References
Learning from Demonstration Using GMM, CHMM and DHMM: A Comparison
1 Introduction
1.1 Safety and Efficiency
2 Current Robot Learning
2.1 Reinforcement Learning
2.2 Learning from Demonstration
3 Environment and Metrics
3.1 Experimental Setup
3.2 Training
3.3 Environmental Modifications
3.4 Metrics
4 Experiment Results and Discussion
4.1 Segment A
4.2 Segment B
4.3 Segment C
5 Conclusion
References
Implementing Modal Tableaux Using Sentential Decision Diagrams
1 Introduction
2 Preliminaries
2.1 Motivation for SDDs
2.2 Constructing SDDs
2.3 Modal Tableaux
3 Method
3.1 Preliminary Experiment: Propositional Compilation
3.2 Theorem Proving
4 Results
4.1 Preliminary Results
4.2 Theorem Proving Results
5 Conclusions and Further Work
References
Decision Making Strategy Based on Time Series Data of Voting Behavior
Abstract
1 Introduction
2 Our Goal in This Study
3 Related Work
3.1 Studies on Horse Racing Investment Strategy Around the World
3.2 Studies on Horse Racing Market in Japan
4 Knowledge Peeping in the Horse Racing
4.1 Knowledge Peeping from Insiders' Votes
4.2 Conditions of Racehorse Extraction Proposed by Law and Peel
4.3 The Method of Determining the Opening Odds
5 Experiments
5.1 Application to the Racing Events Held by JRA
5.2 Expected Rate of Return Without Knowledge Peeping
5.3 Optimization of Parameters Related to Knowledge Peeping
5.4 Visualization of the Expected Rate of Return
6 Discussion
7 Conclusions
References
Finding Within-Organisation Spatial Information on the Web
Abstract
1 Introduction
2 HTML Structure Pattern Learning
3 Spatial Information Extraction
4 Spatial Information Tagging
5 Experiments
5.1 Data Set
5.2 Results
6 Conclusions and Future Work
References
Knowledge Sharing in Coalitions
1 Introduction
2 A Motivating Example
3 The Framework
3.1 Syntax of ATL
3.2 Semantics of ATL
3.3 Properties of the New Semantics
4 The Fixed-Point Characterization
5 Related Work
6 Conclusion
References
Possibilistic Inferences in Answer Set Programming
1 Introduction
2 Preliminaries
2.1 Possibilistic Logic
2.2 Possibilistic ASP (PASP)
3 Possibilistic Inferences in ASP
4 Completion and Loop Formulas for PASP
5 Guarded Resolution for PASP
6 Discussions and Conclusion
References
A Two Tiered Finite Mixture Modelling Framework to Cluster Customers on EFTPOS Network
Abstract
1 Introduction
2 Customer Segmentation Using Finite Mixture Modelling
3 Proposed Customer Segmentation Framework
4 EFTPOS Data Exploration
5 Experimental Design
5.1 Design of Transaction Clustering and Customer Segmentation
6 Experimental Design
6.1 Design of Transaction Clustering and Customer Segmentation
6.2 Experimental Result Analysis
7 Results and Discussions
8 Conclusion and Future Work
References
A Dual Network for Transfer Learning with Spike Train Data
1 Introduction
2 Existing Approaches to Transfer Learning
3 State-Based Dual Network Connectionist Model
3.1 Environment Model
3.2 State Model
4 Operation of the Dual Network Model
4.1 Environment Model Construction through Timespan Search
4.2 State Model Evolution through Recognition
5 Experimentation and Results
5.1 Transfer Learning in a Moving Shape Environment
5.2 Example to Demonstrate How Transfer Learning Occurs
6 Conclusion
References
Stable Feature Selection with Support Vector Machines
1 Introduction
2 Framework
2.1 Algorithm for Covariance-SVM
3 Experiments
3.1 Tuning Parameter Selection
3.2 Performance Metrics
3.3 Simulation Results
3.4 Application on Real Datasets
4 Conclusion
References
Gene Transfer: A Novel Genetic Operator for Discovering Diverse-Frequent Patterns
1 Introduction
2 The Problem Model
3 Related Work
4 Our Approach
4.1 The Genetic Algorithm (GA) Framework
4.2 Gene Transfer Operation
5 Experimental Results
5.1 Dataset
5.2 Results
5.3 Analysis
6 Conclusion
References
Task Allocation Using Particle Swarm Optimisation and Anomaly Detection to Generate a Dynamic Fitness Function
1 Introduction
2 Background and Literature Review
2.1 Anomaly Detection
2.2 Particle Swarm Optimisation
3 Integrating Anomaly Detection for Fitness Function Generation in PSO
4 Experimental Evaluation in a Workplace Hazard Detection Simulation
4.1 Experiment 1: Anomaly Detection Processing Time
4.2 Experiment 2: Minimum Anomaly Size
4.3 Experiment 3: Anomaly Detection and PSO
5 Conclusion and Future
References
Evolving High Fidelity Low Complexity Sheepdog Herding Simulations Using a Machine Learner Fitness Function Surrogate for Human Judgement
1 Introduction
2 Related Work
3 Sheepdog Herding Behaviour Model
4 Experimental Approach
5 Experimental Results and Discussion
5.1 Obtaining Human Evaluations
5.2 Training a Machine Learning System
5.3 Evolving Sheepdog Herding Dynamics
6 Conclusions and Future Work
References
An Episodic Memory Retrieval Algorithm for the Soar Cognitive Architecture
1 Introduction
1.1 The Soar Cognitive Architecture
1.2 Soar Episodic Memory
1.3 Contributions
2 A New Episodic Memory Retrieval Algorithm
2.1 EpMem Encoding
2.2 Cue Matching
2.3 EpMem Retrieval
2.4 Temporal Match
3 Experiments
3.1 Results
3.2 Significance
4 Conclusion
References
Finding the k in K-means Clustering: A Comparative Analysis Approach
1 Introduction
2 Inequality-Based Data Analysis
3 Clustering Traffic Data
4 Conclusions
References
Discovering Causal Structures from Time Series Data via Enhanced Granger Causality
Abstract
1 Introduction
2 Related Work
3 Methodology
3.1 Local Distribution Shift Detection
3.2 The Proposed Regularized Loss Function
3.3 Enhanced Granger Causality
4 Experimental Evaluation
4.1 Datasets and Performance Measures
4.2 Experimental Results and Analysis
5 Conclusions
References
Automating Marine Mammal Detection in Aerial Images Captured During Wildlife Surveys: A Deep Learning Approach
1 Introduction
2 System Overview
3 Region Proposals
4 Convolutional Neural Network Architecture
5 Experimental Results
6 Conclusion
References
Path Algebra for Mobile Robots
1 Introduction
2 Related Work
3 Route Representation
3.1 Forward Route
3.2 Return Route
3.3 Route Simplification
4 Navigation Applications
4.1 Navigation on Trees
4.2 Navigation on Graphs with Cycles
5 Experiments
6 Conclusion
References
Abduction in PDT Logic
1 Introduction and Related Work
2 PDT Logic
2.1 Kripke Structures
2.2 Subjective Posterior Temporal Probabilistic Interpretations
2.3 The Belief Operator
3 Abduction in PDT Logic
3.1 The Hypotheses Space H
3.2 The Abduction Process
4 Conclusion
References
Exploiting Innocuousness in Bayesian Networks
1 Introduction
2 Activator Dynamic Bayesian Networks (ADBN)
3 Innocuousness
4 Exploiting Innocousness
5 Discussion and Comparison
6 Conclusion
References
A Tweet Classification Model Based on Dynamic and Static Component Topic Vectors
1 Introduction
2 Background
3 Model Description and Experiment
4 Ranking Results and Discussion
5 Conclusion and Future Work
References
Understanding Toxicities and Complications of Cancer Treatment: A Data Mining Approach
1 Introduction
2 Related Work
3 Methods
3.1 Clinical Dataset
3.2 Data Pre-processing
3.3 Pairwise Association Analysis
3.4 Association Rule Analysis
3.5 Visualization of Comorbidities
4 Results and Discussion
4.1 One Week
4.2 One Month
5 Conclusion and Future Work
References
A Representation Theorem for Spatial Relations
1 Introduction
2 Partitions and Spatially Relatedness
3 Spatially Relatedness vs. Proximity
4 The Upshift Operator
5 The Main Axioms
5.1 Spatially Relatedness is Grounded
5.2 Alignment of Upshift Close-Ups
5.3 Isolated Points
5.4 Splittings
6 Representation Theorem
7 Related Work
8 Conclusion and Outlook
References
Stream-Query Compilation with Ontologies
1 Introduction
2 Logical Preliminaries
3 The STARQL Framework
4 Separation-Based versus Holistic Semantics
5 Comparison with TCQs
6 Conclusion
References
Vote Counting as Mathematical Proof
1 Introduction
2 First Past the Post Vote Counting
3 Single Transferable Vote
4 Discussion
References
Answer Presentation with Contextual Information: A Case Study Using Syntactic and Semantic Models
1 Introduction
2 Content Selection Using Weighted Triples
2.1 Problem as a Bag of Words
2.2 Problem as a Bag of Concepts
2.3 Domain Corpus
2.4 Reference Corpus
2.5 Triple Retrieval
2.6 Threshold Based Selection
3 Experimental Framework
3.1 Dataset
3.2 Results and Discussion
4 Related Work
5 Conclusion
References
A Multi-Agent Approach for Decentralized Voltage Regulation by Considering Distributed Generators
1 Introduction
2 Voltage Regulation Considering Distributed Generators
2.1 Principle
2.2 Objectives and Constraints
3 A Multi-Agent Approach
3.1 Principle of the Proposed Approach
3.2 Agent Design
3.3 Mechanism Design
3.4 System Development
4 Simulation
5 Conclusion and Future Work
References
Turning Gaming EEG Peripherals into Trainable Brain Computer Interfaces
1 Introduction
2 Related Work
3 Stimulus Classification with the Emotiv EPOC
3.1 Experimental Setup
4 Experimental Results
4.1 Support Vector Machine
4.2 Decision Tree
4.3 K-Nearest Neighbors
5 Discussion
6 Conclusion
References
Event Classification Using Adaptive Cluster-Based Ensemble Learning of Streaming Sensor Data
1 Introduction
2 ACBEstreaming: Our Approach
2.1 Adaptive Windowing Model
2.2 Feature Vector Formation
2.3 On-line Clustering
2.4 Creating the Base Classifier
2.5 Classifier Outputs
3 Results and Discussion
4 Conclusion
References
Standoff-Balancing: A Novel Class Imbalance Treatment Method Inspired by Military Strategy
1 Introduction
1.1 Main Contributions
2 Previous Work
2.1 Class Imbalance Treatment Methods
2.2 Lanchester's Laws
3 Our Method
3.1 Analogy Between Class Imbalance and War
3.2 Standoff-Balancing
4 Experimental Results
5 Conclusion
References
Wisdom of Crowds: An Empirical Study of Ensemble-Based Feature Selection Strategies
1 Introduction
2 Experimental Design
3 Results
4 Conclusion
References
Modeling Ice Storm Climatology
1 Introduction
2 Related Work
3 Materials and Methods
3.1 Ice Storm Climatology
3.2 Data Selection
3.3 Experimental Framework
4 Experimental Results
5 Conclusions and Future Work
References
Investigating Japanese Ijime (Bullying) Behavior Using Agent-Based and System Dynamics Models
Abstract
1 Introduction
2 Agent-Based Model
3 System Dynamics Model
4 Experiments and Results
5 Discussion and Conclusion
References
On the Krom Extension of CFDI-nc
1 Introduction
2 The Description Logic CFDInc
3 TBox Consistency and Concept Satisfiability
4 ABox Reasoning and K Satisfiability
5 Related Work and Summary Comments
References
Understanding People Relationship: Analysis of Digitised Historical Newspaper Articles
Abstract
1 Introduction
2 Methods and Experiments
2.1 Acquisition of Datasets
2.2 Data Pre-processing
3 Association Rules of Person Names
3.1 Measuring Interestingness of Associations
3.2 Closed and Maximal Namesets
3.3 Rules from Closed and Maximal Namesets
3.4 Interestingness of CFI Rules
3.5 Modularity and Average Degree Scores
3.6 Visualising Association Rules
3.7 Categorisation of Querysets
4 Discussion and Conclusions
Acknowledgements
References
Towards the Elimination of the Miscommunication Between Users in Twitter
Abstract
1 Introduction
2 Related Work
3 Proposed Method
3.1 Classification Based on Expected Responses by User
3.2 Definition of Categories
3.3 Training of Classifier
4 Experimental Evaluation
4.1 Experimental Method
4.2 Experimental Result
4.3 Discussion
5 Conclusion
References
Reinforcement Learning of Pareto-Optimal Multiobjective Policies Using Steering
1 Introduction
2 Background
3 Stochastic or Non-stationary MORL Approaches
4 Applying Steering to Pareto-Optimal MORL
5 Empirical Evaluation of w-Steering and Q-Steering
6 Conclusion and Future Work
References
Absorption for ABoxes and TBoxes with General Value Restrictions
1 Introduction
2 Preliminaries
3 Absorption for ABoxes and TBoxes with Local Universal Restrictions
4 Experimental Evaluation
5 Related Work and Summary
References
Optimal Hyper-Parameter Search in Support Vector Machines Using Bézier Surfaces
1 Introduction
2 Hyper-Parameters in Support Vector Machines
3 Hyper-Parameter Search with Bézier Surfaces
3.1 MSE as the Estimation of Variance
3.2 Bézier Surface and -percent region
3.3 Search Strategy
4 Experiment
5 Discussion and Conclusion
References
Hierarchical Learning for Emergence of Social Norms in Networked Multiagent Systems
1 Introduction
2 Social Norms and Reinforcement Learning
3 The Proposed Learning Framework
3.1 Overview of the Hierarchical Learning Framework
3.2 The Hierarchical Learning Mechanism
4 Experiment and Results
4.1 Experimental Setting
4.2 Results and Analysis
5 Related Work
6 Conclusions and Future Work
References
Information Extraction to Improve Standard Compliance
Abstract
1 Introduction
2 Materials and Methods
3 Results
References
Author Index

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