Program

Conference Program

AI 2015 – Schedule of Events

Date Event
November 30, 2015 Doctoral Consortium
December 1, 2015 Workshop and Tutorial
December 2-4, 2015 Conference

 

Conference Schedule is available download as a PDF file HERE, and it is also accessible by CONFERENCEDAY APP.
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The online proceedings of AI 2015 is available here

Workshops and Tutorials

Tuesday, 1st December
Room
Time Studio 1 Combined Studio 2-3 Studio 4
8:00-
Registration
9:00-10:30   Tutorial: Deep Learning  
10:30-11:00
Morning Tea Level 1 Foyer
11:00-12:30 Workshop: KR Conventicle 2015 - In memory of Prof. Norman Foo (1943 – 2015) Workshop: Deep Learning and its Applications in Vision and Robotics Tutorial: Mathematical Optimization in Supply Chain Logistics
12:30-14:00
Lunch Level 1 Foyer
14:00-15:30 Tutorial: Fundamentals of Computational Social Choice
15:30-16:00
Afternoon Tea Level 1 Foyer
16:00-17:30 Tutorial: A Data Analytics View of Genomics

Conference

Wednesday, 2nd December
    Conference Stream
   
A
B
   
Ballroom 2
Ballroom 3
Time      
8:00- Registration  
8:50-9:00 Opening   Conference Opening
9:00-10:00 Keynote   Toby Walsh
10:00-10:30 Morning Tea
Level 1 Foyer
10:30-12:15 Session 1 Data Analytics Social Aspects of AI
12:15-14:00 Lunch
Capitol Grill restaurant, QT ground floor
14:00-15:30 Session 2 Machine Learning 1 Knowledge Representation 1
15:30-16:00 Afternoon Tea
Level 1 Foyer
16:00-17:30 Session 3 Machine Learning 2 Knowledge Representation 2
Thursday, 3rd December
    Conference Stream
    A B
    Ballroom 2 Ballroom 3
Time      
8:45- Registration  
9:00-10:00 Keynote   Wolfram Burgard
10:00-10:30 Morning Tea
Level 1 Foyer
10:30-12:15 Session 4 Social Networks Knowledge Representation 3
12:15-14:00 Lunch
Capitol Grill restaurant, QT ground floor
14:00-15:30 Session 5 Evolutionary algorithms Agents
15:30-16:00 Afternoon Tea
Level 1 Foyer
16:00-17:40 Session 6 Search Robotics and Automation (joint with ACRA)
18:30- Dinner
National Museum of Australia
Friday, 4th December
    Conference Stream
    A B
    Ballroom 2 Ballroom 3
Time      
8:45- Registration  
9:00-10:00 Keynote   Kate Smith Miles
10:00-10:30 Morning Tea
Level 1 Foyer
10:30-11:45 Session 7 Machine Learning 3 Knowledge Representation 4
12:00-14:00 Lunch
QT VIP Lounge
14:00-16:00 Closing Session
Social gathering in the QT VIP Lounge

Workshops

Tutorials

Keynote Presentations

  • Professor Toby Walsh, University of New South Wales – Profile
  • Professor Wolfram Burgard, Albert-Ludwigs-Universität Freiburg – Profile
  • Professor Kate Smith Miles, Monash University – Profile

Conference Sessions

 

Session 1A


77 L Ahmad Shahi, Brendon Woodford and Jeremiah Deng Event Classification using Adaptive Cluster-Based Ensemble Learning of Streaming Sensor Data
7 L Ling Luo, Wei Liu,Irena Koprinska and Fang Chen Discovering Causal Structures from Time Series Data via Enhanced Granger Causality
55 L Dang Nguyen, Wei Luo, Dinh Phung and Svetha Venkatesh Understanding toxicities and complications of cancer treatment: A data mining approach
91 S Yuan Jin and Grace Rumantir A Two Tiered Finite Mixture Modelling Framework to Cluster Customers on EFTPOS Network
46 S Markus Lumpe and Quoc Bao Vo Finding the k in K-means Clustering: A Comparative Analysis Approach

 

Session 1B


87 L Shogo Higuchi, Ryohei Orihara, Yuichi Sei, Yasuyuki Tahara and Akihiko Ohsuga Decision Making Strategy Based on Time Series Data of Voting Behavior
34 L Dirk Pattinson and Carsten Schuermann Vote Counting as Mathematical Proof
53 L Guifei Jiang, Dongmo Zhang and Laurent Perrussel Knowledge Sharing in Coalitions
71 S Michael Siers and Md Zahidul Islam Standoff-Balancing: A novel class imbalance treatment method inspired by military strategy
48 S Chaiwat Thawiworadilok, Mohsen Jafari Songhori and Takao Terano Investigating Japanese Ijime (bullying) behaviour using Agent-Based and System Dynamics Models

 

Session 2A


35 L Sam Fletcher and Md Zahidul Islam A Differentially Private Random Decision Forest using Reliable Signal-to-Noise Ratios
56 L Keith Johnson and Wei Liu A dual network for transfer learning with spike train data
54 L Fenglu Ge, Wayne Moore and Michael Antolovich Learning from Demonstration using GMM, CHMM and DHMM: A Comparison
75 S Liyuan Zhou andHanna Suominen Information Extraction to Improve Standard Compliance: The Case of Clinical Handover

 

Session 2B


30SDavid BillingtonA Propositional Plausible Logic

12 L Karsten Martiny andRalf Möller Abduction in PDT Logic
80 L Francis Li, Jesse Frost and Braden J. Phillips An Episodic Memory Retrieval Algorithm for the Soar Cognitive Architecture
41 L Rajeev Gore, Jason Li and Thomas Pagram Implementing Modal Tableaux using Sentential Decision Diagrams

 

Session 3A


70 L Kylie Chen, Yun Sing Koh and Patricia Riddle Tracking Drift Severity in Data Streams
82 L Teo Susnjak, David Kerry, Andre L. C. Barczak, Napoleon Reyes and Yaniv Gal Wisdom of Crowds: An Empirical Study of Ensemble-based Feature Selection Strategies
43 L Iman Kamkar, Sunil Gupta, Dinh Phungand Svetha Venkatesh Stable Feature Selection with Support Vector Machines
72 S Shinichi Yamada, Kourosh Neshatian and Raazesh Sainudiin Optimal Hyper-parameter Search in Support Vector Machines Using Bezier Surfaces

 

Session 3B


36 L Özgür Lütfü Özcep A Representation Theorem for Spatial Relations
14 L Frederic Maire and Gavin Suddrey Path Algebra for Mobile Robots
68 L Ranjini Swaminathan, Mohan Sridharan, Gillian Dobbie and Katharine Hayhoe Modeling Ice Storm Climatology
21 S Jun Hou, Ruth Schulz, Gordon Wyeth and Richi Nayak Finding Within-Organisation Spatial Information on the Web

 

Session 4A


88 S Tomoaki Ueda,Ryohei Orihara,Yuichi Sei, Yasuyuki Tahara and Akihiko Ohsuga Towards the Elimination of the Miscommunication between Users in Twitter : Tweet classification based on expected responses by user
18 L Alphan Culha andAndrew Skabar Graph-based Collaborative Filtering using Rating Nodes: a Solution to the High Ratings/Low Ratings Problem
57 L Sharon Torao-Pingiand Richi Nayak Understanding People Relationship: Analysis of Digitised Historical Newspaper Articles
85 L Ahmad Abdel-Hafez and Yue Xu Exploiting the Beta Distribution-Based Reputation Model in Recommender System
10 S Parma Nand, Rivindu Perera and Gisela Klette A Tweet Classification Model Based on Dynamic and Static Component Topic Vectors

 

Session 4B


26 S Rivindu Perera and Parma Nand Answer Presentation with Contextual Information: A Case Study using Syntactic and Semantic Models
52 L Jiewen Wu, Taras Kinash, David Tomanand Grant Weddell Absorption for ABoxes and TBoxes with General Value Restrictions
49 L Franz Baader, Stefan Borgwardt and Marcel Lippmann Temporal Conjunctive Queries in Expressive Description Logics with Transitive Roles
51 L David Toman andGrant Weddell On the Krom Extension of CFDInc
78 S Özgür Lütfü Özcep,Ralf Möller and Christian Neuenstadt Stream-Query Compilation with Ontologies

 

Session 5A


97 L Kavitesh Bali andRohitash Chandra Scaling up Multi-Island Competitive Cooperative Coevolution for Real Parameter Global Optimization
45 L Erandi Lakshika, Michael Barlow and Adam Easton Evolving High Fidelity Low Complexity Sheepdog Herding Simulations Using a Machine Learner Fitness Function Surrogate for Human Judgement
3 L Kalyan Shankar Bhattacharjee and Tapabrata Ray An Evolutionary Algorithm with Classifier Guided Constraint Evaluation Strategy for Computationally Expensive Optimization Problems
79 S Shanjida Khatun, Hasib Ul Alam,Mahmood A Rashidand Swakkhar Shatabda GeneTransfer: A Novel Genetic Operator for Discovering Diverse-Frequent Patterns

 

Session 5B


92 L Satyendra Singh Chouhan and Rajdeep Niyogi DMAPP: A Distributed Multi-Agent Path Planning Algorithm
31 L Fenghui Ren, Minjie Zhang and Chao Yu A Multi-Agent Approach for Decentralized Voltage Regulation by Considering Distributed Generators
28 L Chao Yu, Hongtao Lv, Fenghui Ren, Honglin Bao and Jianye Hao Hierarchical Learning for Emergence of Social Norms in Networked Multiagent Systems
40 S Aodah Diamah, Michael Wagner and Menkes van den Briel A comparative study on vector similarity methods for offer generation in multi-attribute negotiation

 

Session 6A


22 L Cameron Browne and Frederic Maire Monte Carlo Analysis of a Puzzle Game
100 S Rubai Ameen and Sameer Alam A Heuristic Search Approach to find Contrail Avoidance Flight Routes
38 S Tom Everitt andMarcus Hutter Analytical Results on the BFS vs. DFS Algorithm Selection Problem. Part I: Tree Search
39 L Tom Everitt andMarcus Hutter Analytical Results on the BFS vs. DFS Algorithm Selection Problem. Part II: Graph Search

 

Session 6B


32 L Reza Farid Region-Growing Planar Segmentation for Robot Action Planning
59 S Frederic Maire, Luis Mejias Alvarez and Amanda Hodgson Automating Marine Mammal Detection in Aerial Images Captured During Wildlife Surveys: a Deep Learning Approach
63 S Manisha Senadeera, Frederic Maire and Andry Rakotonirainy Turning Gaming EEG Peripherals into Trainable Brain Computer Interfaces
  S ACRA TBD  
  S ACRA TBD  
  S ACRA TBD  

 

Session 7A


23 L Peter Vamplew, Rustam Issabekov, Richard Dazeley and Cameron Foale Reinforcement Learning of Pareto-Optimal Multiobjective Policies Using Steering
4 L Kalyan Shankar Bhattacharjee and Tapabrata Ray Cost to evaluate versus Cost to learn ? Performance of selective evaluation strategies in Multiobjective Optimization
33 L Adam Klyne and Kathryn Merrick Task Allocation Using Particle Swarm Optimisation and Anomaly Detection to Generate a Dynamic Fitness Function

 

Session 7B


60 L Kinzang Chhogyal,Abhaya Nayak and Abdul Sattar Probabilistic Belief Contraction: Considerations on epistemic entrenchment, probability mixtures and KL divergence
15 L Yifan Jin, Kewen Wang and Zhe Wang Possibilistic Inferences in Answer Set Programming
20 L Alexander Motzek and Ralf Möller Exploiting Innocuousness in Bayesian Networks