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Showing 1 to 8 of 8 for “"reasoning and learning"”.

  1. Towards Logical Reasoning and Learning in Open and Dynamic Environments

    We live in an increasingly open and dynamic world where knowledge is constantly evolving, and Artificial Intelligence (AI) systems must adapt to newly added information. A crucial aspect of AI systems is performing robust logical reasoning that makes reliable inferences, generates hypotheses, and

    vt Repository record for Towards Logical Reasoning and Learning in Open and Dynamic Environments (opens in a new tab)

  2. Reasoning by Analogy in a Multi-Level System Architecture for the Design of Mechanisms

    … the first attempts to integrate AI technology and engineering design nearly two decades ago, few expert systems have been shown to demonstrate sufficient reasoning capabilities to solve real-world design problems. The complex nature of design, the lack of understanding of the design process, …

    odu Repository record for Reasoning by Analogy in a Multi-Level System Architecture for the Design of Mechanisms (opens in a new tab)

  3. Conditional Preference Networks: Learning and Optimization

    … (AI) addressing issues related to representing, reasoning and learning preferences. One of the main models for graphical representation of preferences is that of Conditional Preference Networks (CP-nets). A CP-net de nes a partial order over the set of outcomes or alternatives by providing a …

    regina Repository record for Conditional Preference Networks: Learning and Optimization (opens in a new tab)

  4. Island Genetic Algorithm-based Cognitive Networks

    The heterogeneity and complexity of modern communication networks demands coupling network nodes with intelligence to perceive and adapt to different network conditions autonomously. Cognitive Networking is an emerging networking research area that aims to achieve this goal by applying distributed …

    vt Repository record for Island Genetic Algorithm-based Cognitive Networks (opens in a new tab)

  5. Structured model learning for adaptive robot generalists

    … move from factories into homes, hospitals, and warehouses, the grand challenge is to create adaptive robot generalists: systems that can learn diverse manipulation skills, transfer knowledge across tasks and embodiments, and operate robustly under varying sensing conditions. However, robotic …

    uiuc Repository record for Structured model learning for adaptive robot generalists (opens in a new tab)

  6. Autonomy through real-time learning and OpenNARS for Applications

    … the autonomy of intelligent agents via real-time learning.In nature, the ability to learn at runtime gives species which can do so key advantages over others. While most AI systems do not need to have this ability but can be trained before deployment, it allows agents to adapt, at runtime, to …

    temple Repository record for Autonomy through real-time learning and OpenNARS for Applications (opens in a new tab)

  7. A neural-symbolic system for temporal reasoning with application to model verification and learning

    … integration of knowledge representation, reasoning and learning into a robust computational model is one of the key challenges in Computer Science and Artificial Intelligence. In particular, temporal models have been fundamental in describing the behaviour of Computational and

    city-london Repository record for A neural-symbolic system for temporal reasoning with application to model verification and learning (opens in a new tab)

  8. Cognitive Networks: Foundations to Applications

    Fueled by the rapid advancement in digital and wireless technologies, the ever-increasing capabilities of wireless devices have placed upon us a tremendous challenge - how to put all of this capability to effective use. Individually, wireless devices have outpaced the ability of users to optimally …

    vt Repository record for Cognitive Networks: Foundations to Applications (opens in a new tab)