Wednesday, 15 November 2017

CFP: WCCI 2018 Special Session: Computational Intelligence for the Automated Design of Machine Learning and Search (CIAD 2018)

Aims, Scope and List of Topics:

Machine learning and search algorithms play an imperative role in solving real world problems in industry and business sectors. Systems employing these techniques have contributed to many facets of industry including data mining, transportation, health systems, computer vision, computer security, robotics, software engineering and scheduling amongst others. These systems employ one or more techniques such as neural networks, fuzzy logic, evolutionary algorithms, multi-agent approaches and rule-based systems. Implementation of these techniques require a number of design decisions to be made, e.g. what architecture to use, what parameter values to use, and derivation of problem specific operators. It may also be necessary to employ a hybrid system combining techniques to solve a problem which introduces additional decisions such as which techniques to use and how to combine these techniques. This makes the development of computational systems time consuming, requiring many person-hours. Consequently, there have been a number of initiatives to automate these processes using computational intelligence.

There has been a fair amount of research into parameter tuning and control. The field of auto-ML aims to automate the design of machine learning algorithms so as to produce off-the-shelf machine learning techniques. Attempts to automate neural network architecture design has led to the field of neuroevolution. Research in this area has also been directed at inducing fuzzy functions, rule-based systems and multi-agent architectures. Hyper-heuristics, which were initially aimed at providing generalized solutions to combinatorial optimization problems, are shown to be effective in the automated design of search techniques. Evolutionary algorithms such as genetic programming and genetic algorithms have made a valuable contribution to this field. The aim of this special session is to examine and promote recent developments in the field and future directions including the challenges and how these can be overcome.

The topics covered include, but are not limited to the following:

* Architecture design, e.g. design of neural networks and multi-agent architectures
* Automated hybridization of intelligent techniques
* Auto-ML
* Automatic programming
* Derivation of constructive heuristics
* Derivation of evaluation functions
* Derivation of operators
* Explainable machine learning
* Hyper-heuristics
* Neuroevolution
* Parameter control and tuning
* Search-based software engineering
* Self*-search


Nelishia Pillay,
University of Pretoria, South Africa

Rong Qu,
University of Nottingham, UK

Important Dates:

Paper submission deadline: 15 January, 2018
Paper acceptance notification: 15 March, 2018
Final paper submission deadline: 1 May, 2018
Early registration: 1 May, 2018

Paper Submission:

Special session papers are treated the same as regular papers and must be submitted via the WCCI 2018 submission website. When submitting choose the " Computational Intelligence for the Automated Design of Machine Learning and Search " special session from the "Main Research Topic" list.

Monday, 13 November 2017

Webinar: Bridge: a New Challenge for AI? – Véronique Ventos (Nov 20)


Dr. Veronique Ventos, Associate Professor, University Paris Saclay Abstract

Games have always been an excellent field of experimentation for the nascent techniques in computer science and in different areas of Artificial Intelligence including Machine Learning. Despite their complexity, game problems are much easier to understand and to model than real life problems. Systems initially designed for games are then used in the context of real applications. In the last decades, designs of champion-level systems dedicated to a game (game AI) were considered as milestones of computer science and AI.
The first part of the webinar is devoted to the presentation of the different aspects of bridge and of various challenges inherent to it.
In a second part, we will present our work concerning the optimization of the AI Wbridge5 developed by Yves Costel. This work is based on a recent seed methodology which optimizes the quality of Monte-Carlo simulations and which has been defined and validated in other games. The Wbridge5 version boosted with this method won the World Computer-Bridge Championship twice, in September 2016 and in August 2017.
Finally, the last part is about various ongoing works related to the design of a hybrid architecture entirely dedicated to bridge using recent numeric and symbolic Machine Learning modules. Biography

PhD in Artificial Intelligence (Knowledge Representation and Machine Learning) in 1997. Associate professor at University Paris Saclay, France since 1998. Before joining in 2015 the group A&O in the interplay of Machine Learning and Optimization, she worked in the group LaHDAK (Large-scale Heterogeneous DAta and Knowledge) at Laboratory of Computer Science (LRI). She started playing bridge in 2004 and is now 59th French woman player out of 48644 players. In 2015, she set up the AlphaBridge project combining her two passions. AlphaBridge is dedicated to solve the game of bridge by defining a hybrid architecture including recent numeric and symbolic ML modules.

Register at:

CFP: IEEE World Congress on Computational Intelligence (WCCI 2018) (Jan 15, 2018)

Call for Papers

On behalf of the IEEE WCCI 2018 Organizing Committee, it is our great pleasure to invite you to the bi-annual IEEE World Congress on Computational Intelligence (IEEE WCCI), which is the largest technical event in the field of computational intelligence. The IEEE WCCI 2018 will host three conferences: The 2018 International Joint Conference on Neural Networks (IJCNN 2018 – co-sponsored by International Neural Network Society – INNS), the 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2018), and the 2018 IEEE Congress on Evolutionary Computation (IEEE CEC 2018) under one roof. It encourages cross-fertilization of ideas among the three big areas and provides a forum for intellectuals from all over the world to discuss and present their research findings on computational intelligence.
IEEE WCCI 2018 will be held at the Windsor Convention Centre, Rio de Janeiro, Brazil. Rio de Janeiro is one of the most attractive cities in South America, with the largest urban forest in the world, beautiful bays, lagoons and 90 kms of beaches and mountains. Known as one of the most beautiful cities in the World, Rio de Janeiro is the first city to receive the certificate of World Heritage for its Cultural Landscape. This unprecedented title was recently conferred by the United Nations Educational, Cultural and Scientific Organization (UNESCO).
Rio de Janeiro is easily accessible from all over the world, with direct flights from major cities in North America, Europe, Africa and Middle East. It is also a one stop away from Asia and Australia. The venue, The Windsor Barra Complex, features a brand new Convention Center and three different categories hotels, in the fastest growing region in Rio de Janeiro, with walking distance from a great choice of restaurants and shopping centers.
IEEE Computational Intelligence Society has maintained its position as a leader of journals in computational intelligence. CIS journals sustained their status as premier scholarly publications, earning high rankings in the Journal Citation Report by Thomson Reuters.
  • IEEE Transactions on Neural Networks and Learning Systems (IF: 4.854)
  • IEEE Transactions on Fuzzy Systems (IF: 6.701)
  • IEEE Transactions on Evolutionary Computation (IF: 5.908)
  • IEEE Computational Intelligence Magazine (IF: 3.647)

List of topics:


  • Algorithms
    • Ant colony optimization
    • Artificial immune systems
    • Coevolutionary systems
    • Cultural algorithms
    • Differential evolution
    • Estimation of distribution algorithms
    • Evolutionary programming
    • Evolution strategies
    • Genetic algorithms
    • Genetic programming
    • Heuristics, metaheuristics and hyper-heuristics
    • Interactive evolutionary computation
    • Learning classifier systems
    • Memetic, multi-meme and hybrid algorithms
    • Molecular and quantum computing
    • Multi-objective evolutionary algorithms
    • Parallel and distributed algorithms
    • Particle swarm optimization
  • Theory and Implementation
    • Adaptive dynamic programming and reinforcement learning
    • Autonomous mental development
    • Coevolution and collective behavior
    • Convergence, scalability and complexity analysis
    • Evolutionary computation theory
    • Representation and operators
    • Self-adaptation in evolutionary computation
  • Optimization
    • Numerical optimization
    • Discrete and combinatorial optimization
    • Multiobjective optimization
  • Handling of Various Aspects
    • Large-scale problems
    • Preference handling
    • Evolutionary simulation-based optimization
    • Meta-modeling and surrogate models
    • Dynamic and uncertain environments
    • Constraint and uncertainty handling
  • Hybrid Systems of Computational Intelligence
    • Evolved neural networks
    • Evolutionary fuzzy systems
    • Evolved neuro-fuzzy systems
  • Related Areas and Applications
    • Art and music
    • Artificial ecology and artificial life
    • Autonomous mental and behavior development
    • Biometrics, bioinformatics and biomedical applications
    • Classification, clustering and data analysis
    • Data mining
    • Defense and cyber security
    • Evolutionary games and multi-agent systems
    • Evolvable hardware and software
    • Evolutionary Robotics
    • Engineering applications
    • Emergent technologies
    • Finance and economics
    • Games
    • Intelligent systems applications
    • Robotics
    • Real-world applications
    • Emerging areas


    • Feedforward neural networks
    • Recurrent neural networks
    • Self-organizing maps
    • Radial basis function networks
    • Attractor neural networks and associative memory
    • Modular networks
    • Fuzzy neural networks
    • Spiking neural networks
    • Reservoir networks (echo-state networks, liquid-state machines, etc.)
    • Large-scale neural networks
    • Learning vector quantization
    • Deep neural networks
    • Randomized neural networks
    • Other topics in artificial neural networks
    • Supervised learning
    • Unsupervised learning and clustering, (including PCA, and ICA)
    • Reinforcement learning and adaptive dynamic programming
    • Semi-supervised learning
    • Online learning
    • Probabilistic and information-theoretic methods
    • Support vector machines and kernel methods
    • EM algorithms
    • Mixture models, ensemble learning, and other meta-learning or committee algorithms
    • Bayesian, belief, causal, and semantic networks
    • Statistical and pattern recognition algorithms
    • Sparse coding and models
    • Visualization of data
    • Feature selection, extraction, and aggregation
    • Evolutionary learning
    • Hybrid learning methods
    • Computational power of neural networks
    • Deep learning
    • Other topics in machine learning
    • Dynamical models of spiking neurons
    • Synchronization and temporal correlation in neural networks
    • Dynamics of neural systems
    • Chaotic neural networks
    • Dynamics of analog networks
    • Itinerant dynamics in neural systems
    • Neural oscillators and oscillator networks
    • Dynamics of attractor networks
    • Other topics in neurodynamics
    • Connectomics
    • Models of large-scale networks in the nervous system
    • Models of neurons and local circuits
    • Models of synaptic learning and synaptic dynamics
    • Models of neuromodulation
    • Brain imaging
    • Analysis of neurophysiological and neuroanatomical data
    • Cognitive neuroscience
    • Models of neural development
    • Models of neurochemical processes
    • Neuroinformatics
    • Other topics in computational neuroscience
    • Neurocognitive networks
    • Cognitive architectures
    • Models of conditioning, reward and behavior
    • Cognitive models of decision-making
    • Embodied cognition
    • Cognitive agents
    • Multi-agent models of group cognition
    • Developmental and evolutionary models of cognition
    • Visual system
    • Auditory system
    • Olfactory system
    • Other sensory systems
    • Attention
    • Learning and memory
    • Spatial cognition, representation and navigation
    • Semantic cognition and language
    • Grounding, symbol grounding
    • Neural models of symbolic processing
    • Reasoning and problem-solving
    • Working memory and cognitive control
    • Emotion and motivation
    • Motor control and action
    • Dynamical models of coordination and behavior
    • Consciousness and awareness
    • Models of sleep and diurnal rhythms
    • Mental disorders
    • Other topics in neural models of perception, cognition and action
    • Brain-machine interfaces
    • Neural prostheses
    • Neuromorphic hardware
    • Embedded neural systems
    • Other topics in neuroengineering
    • Brain-inspired cognitive architectures
    • Embodied robotics
    • Evolutionary robotics
    • Developmental robotics
    • Computational models of development
    • Collective intelligence
    • Swarms
    • Autonomous complex systems
    • Self-configuring systems
    • Self-healing systems
    • Self-aware systems
    • Emotional computation
    • Artificial life
    • Other topics in bio-inspired and biomorphic systems
    • Applications of deep neural networks
    • Bioinformatics
    • Biomedical engineering
    • Data analysis and pattern recognition
    • Speech recognition and speech production
    • Robotics
    • Neurocontrol
    • Approximate dynamic programming, adaptive critics, and Markov decision processes
    • Neural network approaches to optimization
    • Signal processing, image processing, and multi-media
    • Temporal data analysis, prediction, and forecasting; time series analysis
    • Communications and computer networks
    • Data mining and knowledge discovery
    • Power system applications
    • Financial engineering applications
    • Security applications
    • Applications in multi-agent systems and social computing
    • Manufacturing and industrial applications
    • Expert systems
    • Clinical applications
    • Big data applications
    • Other applications
    • Smart grid applications
    • Hybrid intelligent systems
    • Swarm intelligence
    • Sensor networks
    • Quantum computation
    • Computational biology
    • Molecular and DNA computation
    • Computation in tissues and cells
    • Artificial immune systems
    • Philosophical issues
    • Other cross-disciplinary topics


  • Mathematical and theoretical foundations
    • fuzzy measures and fuzzy integrals
    • fuzzy differential equations
    • fuzzy logic, fuzzy inference systems
    • aggregation, operators, fuzzy relations
  • Fuzzy control
    • optimal control of dynamic systems
    • adaptive and dynamically evolving process control
    • networked control systems
    • plantwide, monitoring, and supervisory control
  • Robotics and autonomous systems
    • navigation
    • decision making and situation awareness
    • handling systems
    • automated factories
    • smart industry
  • Fuzzy hardware, software, sensors, actuators, architectures
  • Fuzzy data and analysis
    • clustering, classification and pattern recognition
    • statistics and imprecise probabilities
    • data summarization
    • big data
    • time series modeling and forecasting
    • data analytics and visualization
    • social networks mining and analysis
  • Data management and web engineering
    • fuzzy data modeling
    • databases and information retrieval
    • data aggregation and fusion
    • fuzzy markup languages
  • Granular computing
    • type-2 fuzzy sets
    • intuitionistic fuzzy sets
    • higher order fuzzy sets
    • interval data processing
    • rough sets and relations
    • hybrid granular approaches
    • data clouds
  • Computational and artificial intelligence
    • fuzzy neural networks
    • fuzzy deep learning
    • fuzzy evolutionary algorithms
    • dynamically evolving fuzzy systems
    • fuzzy agent systems
    • knowledge representation and approximate reasoning
    • elicitation of fuzzy sets
    • explainable artificial intelligence
  • Otimization and operations research
    • fuzzy mathematical programming
    • possibilistic optimization
    • fuzzy algorithms and heuristic search
  • Decision analysis, multi-criteria decision making, and decision support
  • Fuzzy modeling, identification, and fault detection
  • Knowledge discovery
  • Fuzzy image, speech and signal processing, vision and multimedia data
  • Linguistic summarization, natural language processing
  • Applications
    • industry, technology, engineering
    • finance, business, economics
    • medicine, biological and social sciences
    • geographical information systems
    • social and communication networks
    • agriculture and environment engineering
    • security and mobility

Important Dates

  • 15 December 2017 – Tutorial, Special Sessions, Workshop and Competition Proposals
  • 15th January 2018 – Paper Submission 
  • 15th March 2018 – Paper Acceptance
  • 1st May 2018 – Final Paper Submission
  • 1st May 2018 – Early Registration
  • 8-13 July 2018 – IEEE WCCI 2018, Rio de Janeiro, Brazil 

CFP: IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2018) (Jan 20, 2018)

The 2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS 2018) will be held in the exotic island of Rhodes (Greece) which has a beautiful medieval town built by the crusaders and it is preserved as UNESCO monument. A main characteristic of Rhodes is its long ancient history with many ancient Greek sites. Set against the historic backdrop of Rhodes island is the elegant and pisturesque lowrise architecture of Aldemar Amilia Mare Village, an all-inclusive seaside resort. Newly refurbished luxury rooms with sea or garden views are the perfect choice for all holidaymakers, from singles to families. Dive into crystal clear swimming pools, try a wide range of watersports at the beach, enjoy the Spa Centre with its fully equipped fitness area and sample the cosmopolitan delights of the themed restaurants.

EAIS 2018 will provide a working and friendly atmosphere and will be a leading international forum focusing on the discussion of recent advances, the exchange of recent innovations and the outline of open important future challenges in the area of Evolving and Adaptive Intelligent Systems.

Over the past decade, this area has emerged to play an important role on a broad international level in today's real-world applications, especially ones with high complexity and dynamics change. Its embedded modelling and learning methodologies are able to cope with real-time demands, changing operation conditions, varying environmental influences, human behaviors, knowledge expansion scenarios and drifts in online data streams.

EAIS 2018 is organized by the IEEE Technical Committee on Evolving and Adaptive Intelligent Systems, SMC Society and the IEEE Computational Intelligence Society.

Special Session Proposals Deadline : 20th of December, 2017

Paper Submission Deadline : 20th of January, 2018

Decision Notification : 15th of February, 2018

Final Paper Submission Deadline : 25th of February, 2018

Authors Registration Deadline : To be announced

Conference : 25 - 27 May, 2018

Friday, 10 November 2017

CFP: IEEE TG Special Issue on Game Competition Frameworks for Research and Education (Jan 8, 2018)

Important Dates
Submission Deadline: 8 January 2018
Notification of Acceptance: 1 April 2018
Final copy due: 31 July 2018
Suggestions for Submissions
We invite the submission of papers about high quality work on game competition frameworks, entry submissions, their use as research testbeds to obtain novel experimental results, or as educational and teaching material. Regular, short and letter papers are invited to this special issue, with the following suggestion for these lengths:
  • Letter papers detailing use of competitions as educational or teaching material OR describing competition entries. Authors are allowed to briefly include the description of the competition framework and rules, but they are encouraged to mainly focus on the main contribution of their work.
  • Short papers with a technical description of the game competition framework (including link to the released code of the benchmark) OR a description of competition entries. For the later case, authors are allowed to briefly include the description of the competition framework and rules, but they are encouraged to mainly focus on the main contribution of their work.
  • Regular papers describing work using a competition benchmark as a research environment for novel experimental results, OR description of the game competition including analysis of the top entries and final results.
Competition organisers and participants are encouraged to communicate and collaborate with each other to avoid duplicating descriptions of framework, rules, entries, etc.
Instructions for Submissions
Authors should follow normal ToG guidelines for their submissions, but clearly identify their papers for this special issue during the submission process. Extended versions of previously published conference or workshop papers are welcome, provided that the journal paper is a significant extension, and is accompanied by a cover letter explaining the additional contribution. See here for author information and page length limit.
Aim & Scope
Games are an ideal domain to study computational intelligence methods because they provide affordable, competitive, dynamic, reproducible environments suitable for testing new search algorithms, pattern-based evaluation methods, or machine learning concepts.Diverse game competitions have been designed for different research purposes and some of them have been successfully organised for 10 years, such as the game Go competition series and PacMan competition series. The past game competitions organised in conferences, industry or as private leagues have covered various games, from single-player board/video games to real-time strategy games. In different competitions, the participants are invited to submit an agent to play a specific game or a set of unknown games without intervention of human at least as good as professional human players, or to submit an agent to design a game or game rules. These have not only received submissions from academic institutions, but also attracted the attention of the games industry. Dozens of universities have used different game competition frameworks in modules of Game Design, Artificial Intelligence or Machine Learning.
The following is a list of suggested, not exclusive, competitions for this special issue:
Angry Birds Level Generation
Computer Game Olympiads (including Chess, Amazons, Backgammon, Bridge, Chinese Chess, Dots and Boxes, Draughts, Go, LOA, Shogi, …)
Dota2 Bot
Fighting Game AI
Game Data Mining
General Video Game AI
Geometry Friends Cooperative Game AI
microRTS AI
Ms. Pac-Man Vs Ghost Team
Showdown AI
StarCraft AI
Text-Based Adventure AI
Visual Doom AI
About the Guest Editors
Jialin Liu is currently a Postdoctoral Research Associate at Queen Mary University of London (UK). She holds a B.Sc. from the Huazhong University of Science and Technology (2010, China), an M.Sc. from the Université Paris-Sud and École Polytechnique (2013, France) and a Ph.D from the Université Paris-Saclay (2016, France). Her research interests include reinforcement learning, black-box noisy optimisation, portfolio algorithms and artificial intelligence in games. She has published more than 20 international conference papers and 4 journal papers in the aforementioned fields, and will be the Program Co-Chair of the IEEE’s 2018 Computational Intelligence on Games, one of the key conferences in the area of game artificial intelligence.
Diego Perez-Liebana is a Lecturer in Computer Games and Artificial Intelligence at the University of Essex (UK), where he achieved a PhD in Computer Science (2015). He holds an MSc and BSc degrees in Computer Science from University Carlos III (Madrid, Spain; 2007). He has published in the domain of Game AI, with interests on Reinforcement Learning and Evolutionary Computation. He organized several Game AI competitions, such as the Physical Traveling Salesman Problem and the General Video Game AI competitions, held in IEEE conferences. He has published more than 45 papers in the field of Game AI, including the main conferences and journals in the field of Computational Intelligence in Games. He has programming experience in the videogames industry with titles published for game consoles and PC.
Tristan Cazenave is a Professor of artificial intelligence at LAMSADE Universite Paris-Dauphine. Author of more than a hundred scientific papers about artificial intelligence in games. He started to publish commercial video games when he was aged 16 and co-founded a successful web agency in 1992. He was the Editor in chief of the ICGA Journal.
About the Associate Editor of ToG
Ruck Thawonmas is a Professor in College of Information Science and Engineering at Ritsumeikan University (Japan), where he is leading the Intelligent Computer Entertainment Laboratory with more than 65 Lab’s graduate-level alumni, around half of which are working in game industry. He has published more than 175 peer-reviewed papers in both Japanese and English; Two papers were cited more than 150 times each (Google Scholar); h-index = 21 (Google Scholar). In addition, his students won a number of prestigious game AI competitions such as the first AIBIRDS Level Generation Champion at the IEEE Conference on Computational Intelligence and Games (IEEE-CIG) 2016, the IEEE-CIG 2014 StarCraft AI Competition, and the AIIDE 2014 StarCraft AI Competition. He is currently an Associate Editor for IEEE Transactions on Computational Intelligence and AI in Games (04/2014—present) as well as Games for Health Journal (07/2014—present).
Jialin Liu – jialin.liu(at)
Diego Perez-Liebana – dperez(at)
Tristan Cazenave – cazenave(at) 
Ruck Thawonmas – ruck(at)