Monday, July 19, 2010

Learning and Intelligent OptimizatioN LION 5, Jan 17-21, 2011, Rome, Italy



LION 5, Learning and Intelligent OptimizatioN,
Rome - Italy, Jan 17-21 201
0

Short call for papers:

The LION conference aims at exploring the intersections between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems. The main purpose of the event is to bring together experts from all these areas to present and discuss new ideas, new methods, general trends, challenges and opportunities in applications as well as in research aiming at algorithmic advances. The conference program will consist of plenary presentations, introductory and advanced tutorials, technical presentations, and it will give ample time for discussions.

Scope of the conference

The large variety of heuristic algorithms for hard optimization problems raises numerous interesting and challenging issues. Practitioners are confronted with the burden of selecting the most appropriate method, in many cases through an expensive algorithm configuration and parameter tuning process, and subject to a steep learning curve. Scientists seek theoretical insights and demand a sound experimental methodology for evaluating algorithms and assessing strengths and weaknesses. A necessary prerequisite for this effort is a clear separation between the algorithm and the experimenter, who, in too many cases, is "in the loop" as a crucial intelligent learning component. Both issues are related to designing and engineering ways of "learning" about the performance of different techniques, and ways of using past experience about the algorithm behavior to improve performance in the future. Intelligent learning schemes for mining the knowledge obtained from different runs or during a single run can improve the algorithm development and design process and simplify the applications of high-performance optimization methods. Combinations of algorithms can further improve the robustness and performance of the individual components provided that sufficient knowledge of the relationship between problem instance characteristics and algorithm performance is obtained.

Important Dates

Submission deadlineOctober 16, 2010
Notification of acceptanceNovember 27, 2010
ConferenceJanuary 17-21, 2011
Camera ready for post-proceedings February 18, 2011

Relevant Research Areas

LION 5 solicits contributions dealing with all aspects of learning and intelligent optimization. Topics of interest include, but are not limited to:

  • Metaheuristics such as tabu search, iterated local search, evolutionary algorithms, memetic algorithms, ant colony optimization, and particle swarm optimization
  • Hybridizations of metaheuristics with other techniques for optimization
  • Supervised, unsupervised and reinforcement learning applied to heuristic search
  • Reactive search optimization
  • Self-adaptive algorithms
  • Hyperheuristics
  • Algorithm portfolios and off-line tuning methods
  • Multiscale and multilevel methods
  • Algorithms for dynamic, stochastic and multi-objective problems
  • Interface(s) between discrete and continuous optimization
  • Experimental analysis and modeling of algorithms
  • Theoretical foundations
  • Parallelization of optimization algorithms
  • Memory-based optimization
  • Software engineering of learning and intelligent optimization methods.

IJCAI-11 22nd International Joint Conference on Artificial Intelligence

Call for papers

The IJCAI-11 Program Committee invites submissions of technical papers for IJCAI-11, to be held in Barcelona, Spain, July 19-22, 2011. Submissions are invited on significant, original, and previously unpublished research on all aspects of artificial intelligence.

The theme of IJCAI-11 is “Integrated and Embedded Artificial Intelligence” (IEAI) with a focus on artificial intelligence that crosses discipline boundaries within AI, and between AI and other disciplines. Building systems often requires techniques from more than one area (e.g. both machine learning and natural language processing, or both planning and preference representation). In addition, larger systems often have AI components embedded within that provide intelligent functionalities such as learning and reasoning. The conference will include a special track dedicated to such work.

Important dates
  • Abstract submission: Jan 19, 2011 (11:59PM, UTC-12)
  • Paper submission: Jan 24, 2011 (11:59PM, UTC-12)
  • Author feedback: Feb 28-Mar 3, 2011 (11:59PM, UTC-12).
  • Notification of acceptance/rejection: Mar 31, 2011
  • Camera-ready copy due: Apr 15, 211
  • Technical sessions: Jul 19-22, 2011

Details

List of keywords

Agent-based and Multiagent Systems

  • Agent Theories and Architectures
  • Agent Communication
  • Agreement Technologies Argumentation
  • Auctions and Market-Based Systems
  • Coordination and Collaboration
  • Distributed AI
  • E-Commerce
  • Game Theory
  • Multiagent Learning
  • Multiagent Planning
  • Multiagent Systems
  • Simulation and Emergent Behavior
  • Social Choice

Constraints, Satisfiability, and Search

  • Applications
  • Constraint Optimization
  • Constraint Satisfaction
  • Distributed Constraints
  • Dynamic Programming
  • Evaluation and Analysis
  • Global Constraints
  • Heuristic Search
  • Meta-heuristics
  • Quantifier Formulations
  • Satisfiability
  • Modeling
  • Search
  • Solvers and Tools
  • Symmetry

Knowledge Representation, Reasoning and Logic

  • Action, Change and Causality
  • Automated Reasoning and Theorem Proving
  • Beliefs and Knowledge
  • Common-Sense Reasoning
  • Computational Complexity
  • Description Logics and Ontologies
  • Diagnosis and Abductive Reasoning
  • Geometric, Spatial, and Temporal Reasoning
  • Knowledge Representation
  • Logic Programming
  • Many-Valued and Fuzzy Logics
  • Nonmonotonic Reasoning
  • Preferences
  • Qualitative Reasoning
  • Reasoning with Beliefs

Machine Learning

  • Active Learning
  • Case-based Reasoning
  • Classification
  • Cost-Sensitive Learning
  • Data Mining
  • Deep Learning
  • Ensemble Methods
  • Evolutionary Computation
  • Feature Selection/Construction
  • Kernel Methods
  • Learning Graphical Models
  • Learning Preferences or Rankings
  • Learning Theory
  • Machine Learning
  • Neural Networks
  • Online Learning
  • Reinforcement Learning
  • Relational Learning
  • Semi-Supervised/Unsupervised Learning
  • Structured Learning
  • Time-series/Data Streams
  • Transfer, Adaptation, Multi-task Learning

Multidisciplinary Topics And Applications

  • AI and Natural Sciences
  • AI and Social Sciences
  • Art and Music
  • AI and Ubiquitous Computing Systems
  • Autonomic Computing
  • Brain Sciences
  • Cognitive Modeling
  • Computational Biology and e-Health
  • Computer Games
  • Computer-Aided Education
  • Human-Computer Interaction
  • Intelligent Database Systems
  • Intelligent User Interfaces
  • Interactive Entertainment
  • Knowledge-based Software Engineering
  • Personalization and User Modeling
  • Philosophical and Ethical Issues
  • Real-Time Systems
  • Security and Privacy
  • Validation and Verification

Natural-Language Processing

  • Dialogue
  • Discourse
  • Information Extraction
  • Information Retrieval
  • Machine Translation
  • Morphology and Phonology
  • Natural Language Generation
  • Natural Language Semantics
  • Natural Language Summarization
  • Natural Language Syntax
  • Natural Language Processing
  • Psycholinguistics
  • Question Answering
  • Speech Recognition and Understanding
  • Text Classification

Planning and Scheduling

  • Activity and Plan Recognition
  • Applications of Planning
  • Conformant/Contingent Planning
  • Hierarchical Task Networks
  • Hybrid Systems
  • Markov Decisions Processes
  • POMDPs
  • Plan Execution and Monitoring
  • Planning Algorithms
  • Planning under Uncertainty
  • Real-time Planning
  • Robot Planning
  • Scheduling
  • Search in Planning and Scheduling
  • Theoretical Foundations of Planning

Robotics and Vision

  • Behavior and Control
  • Cognitive Robotics
  • Human Robot Interaction
  • Localization, Mapping, State Estimation
  • Manipulation
  • Motion and Path Planning
  • Multi-Robot Systems
  • Robotics
  • Sensor Networks
  • Vision and Perception

Uncertainty in AI

  • Approximate Probabilistic Inference
  • Bayesian Networks
  • Decision/Utility Theory
  • Exact Probabilistic Inference
  • Graphical Models
  • Preference Elicitation
  • Sequential Decision Making
  • Uncertainty

Web and Knowledge-based Information Systems

  • Information Extraction
  • Information Integration
  • Information Retrieval
  • Knowledge Acquisition
  • Knowledge Engineering
  • Knowledge-based Systems
  • Ontologies
  • Recommender Systems
  • Semantic Web
  • Social Networks
  • Source Wrapping
  • Web Mining
  • Web Search
  • Web Technologies