Neural Computing & Applications is an international journal which publishes original research and other information in the field of practical applications of neural computing and related techniques such as genetic algorithms, fuzzy logic and neuro-fuzzy systems.  

All items relevant to building practical systems are within its scope, including but not limited to:

    adaptive computing
    algorithms
    applicable neural networks theory
    applied statistics
    architectures
    artificial intelligence
    benchmarks
    case histories of innovative applications
    fuzzy logic
    genetic algorithms
    hardware implementations
    hybrid intelligent systems
    intelligent agents
    intelligent control systems
    intelligent diagnostics
    intelligent forecasting
    machine learning
    neural networks
    neuro-fuzzy systems
    pattern recognition
    performance measures
    self-learning systems
    software simulations
    supervised and unsupervised learning methods
    system engineering and integration

Featured contributions fall into several categories: Original Articles, Review Articles, Book Reviews and Announcements.
The Original Articles will be high-quality contributions, representing new and significant research, developments or applications of practical use and value.  They will be reviewed by at least two referees. 

FOUNDING EDITOR
Howard James

JOURNAL ADMINISTRATOR
Tanya Daly, United Kingdom

For all queries relating to papers after submission, please contact the Journal Editorial Office via “contact us” at Editorial Manager.

Special Issue on Explainable Sequential Decision-Making
截稿日期: 2025-01-01

Aims and Scope

As we work with AI and rely on AI for more and more decisions that influence our lives, the research area of explainable AI (XAI) has rapidly developed, with goals such as increasing trust, enhancing collaboration, and enabling transparency in AI. The focus of this topical collection is on explainable sequential decision-making – XAI for systems that are required to make a sequence of decisions to achieve their goals or objectives. This stands in contrast to the substantial existing work on interpretable machine learning, which generally focuses on the single input-output mappings of "black box" models such as neural networks. While such ML models are an important tool, intelligent behavior extends over time and needs to be explained and understood as such. We may have superhuman chess agents, but can they teach us how to play? We may have search & rescue robots, but can we effectively and efficiently communicate with them in the field?

This topical collection targets high-quality original papers covering all aspects of explainable sequential decision-making. Manuscripts that extend a previous conference or workshop publication are welcome, provided that there is a significant amount (at least 30%) of new material in the submission. Relevant topics include, but are not limited to, the following:

    Explainable/interpretable/intelligible reinforcement learning
    Explainable planning and search
    Explainability in Multi-Agent Systems
    Explainability for and through negotiations or argumentation
    Extended explanatory dialogue with users
    Modeling users over extended interactions
    Explanation-aware sequential decision-making
    Foundational frameworks for formalizing and evaluating explainable agency in sequential decision-making settings
    Integration of explainable agents and explainable deep learning, e.g. when DL models are guiding agent behaviors
    User interfaces/visualizations for explaining agent behavior, learning or planning
    Evaluation methods for explainable sequential decision-making systems
    Explainability for embodied systems/robotics
    Other practical applications for explainability in sequential or goal-oriented tasks, e.g. in planning/scheduling, in pathfinding, etc.
    Policy/plan summarization
    Cognitive theories
    Empirical studies in explainable sequential decision making

Guest Editors

Hendrik Baier (Lead Guest Editor), Eindhoven University of Technology, The Netherlands, h.j.s.baier@tue.nl
Sarath Sreedharan, Colorado State University, USA, ssreedh3@colostate.edu

Manuscript submission deadline: 1st January 2025

Special Issue on Multi-Objective Decision Making 2024 (MODeM 2024)
截稿日期: 2025-02-17

Building on two previous successful topical collections (TCs), we are delighted to invite submissions to a new topical collection of Neural Computing and Applications (NC&A, impact factor 6.0) on Multi-Objective Decision Making 2024 (MODeM 2024).

Previous topical collections in this series were hosted in:

    Neural Computing and Applications - TC on MODeM 2023 (in progress)
    Journal of Autonomous Agents and Multi-Agent Systems - TC on MODeM (completed in 2023)

Explicitly modelling multiple objectives can be essential for decision support, explainability, and human-AI alignment. As such, there has been a growing awareness of the need for automated and assistive decision making systems to move beyond single-objective formulations when dealing with complex real-world issues, which invariably involve multiple competing objectives. In this topical collection, we aim to provide a platform for original research in multi-objective decision making using AI.

This topical collection targets high-quality original papers covering all aspects of multi-objective decision making, including, but not limited to, the list of topics below. Manuscripts that extend a previous conference or workshop publication are welcome, provided that there is a significant amount of new material in the submission (i.e., the manuscript should contain at least 50% new material).

Please note that manuscripts submitted to this TC should have a clear link to artificial intelligence and/or agent-based systems - manuscripts without a clear link to these areas will be desk rejected without being sent for review.

Topics

The following is a non-exhaustive list of topics that we would like to cover in the topical collection:

    Multi-objective/multi-criteria/multi-attribute decision making
    Multi-objective reinforcement learning
    Multi-objective planning and scheduling
    Multi-objective multi-agent decision making
    Multi-objective game theory
    Multi-objective/multi-criteria/multi-attribute utility theory
    Preference elicitation for MODeM
    Social choice and MODeM
    Multi-objective decision support systems
    Multi-objective metaheuristic optimisation (e.g., evolutionary algorithms) for autonomous agents and multi-agent systems
    Multi-objectivisation
    Human-AI alignment through multi-objective modelling
    Ethical AI through multi-objective modelling
    Explainable AI through multi-objective modelling
    Interactive systems for MODeM
    Applications of MODeM
    Interdisciplinary work (MODeM research that relates to other fields)
    New benchmark problems for MODeM

Guest Editors

Roxana Rădulescu (Lead Guest Editor), Utrecht University & Vrije Universiteit Brussel, r.t.radulescu@uu.nl
Patrick Mannion, University of Galway
Pieter Libin, Vrije Universiteit Brussel

Please direct queries about the NC&A MODeM 2024 TC to the Lead Guest Editor at r.t.radulescu@uu.nl

Timeline

Submission deadline: 17th February 2025

Manuscript submissions will be considered for publication in the NC&A MODeM 2024 TC on a continuous basis until the submission deadline. Submissions accepted for publication before the completion of the TC will be available on the journal website shortly after acceptance.