Displaying 4 resources
White paper White paper

Holistic framework for AI in critical network infrastructures

This document establishes the main foundations of the AI4REALNET project, in particular, the following key outcomes: - The formal specification of domain-specific use cases (UCs), replicating real-world operating scenarios involving human operator

Category
Action and Interaction Technologies, Real-time context aware decision making, Policy, Regulation, Certificates, and Standards, Best practices in deployment, Legal framework and regulation, Recommendations towards policy changes, Reasoning and decision-making Technologies, Hybrid Decision Making, Trustworthiness, Systems, methodologies, hardware, and tools, Support tools, System architectures
Target audience
ADR Experts and Associations, Individual Citizens/Members of the Society, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e
White paper White paper

Position paper on AI for the operation of critical energy and mobility network infrastructures

This position paper outlines AI4REALNET’s approach to applying AI in network infrastructure operations, translating application needs into algorithmic proposals for effective human-AI collaboration in decision-making processes.

Category
Action and Interaction Technologies, Real-time context aware decision making, Experiment and Deployment, Fundamental Rights, Principles, and Values, Multistakeholder dialogue, Policy, Regulation, Certificates, and Standards, Best practices in deployment, Reasoning and decision-making Technologies, Hybrid Decision Making, Reasoning Techniques, Trustworthiness, Systems, methodologies, hardware, and tools, Support tools, Technology methodologies and landscape
Target audience
ADR Experts and Associations, Policy Makers, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e
Online Course Online Course

Non-Markov Decision Processes and Reinforcement Learning

We present non-Markov decision processes, where rewards and dynamics can depend on the history of events. This is contrast with Markov Decision Processes, where the dependency is limited to the last state and action.

Category
Hybrid Decision Making
Target audience
ADR Experts and Associations, Researchers and Academic
Source
Adra-e
Online Course Online Course

AI in Middle School Science Topics

Any instance where there is a large amount of data to be examined or processed that would take a lot of time for a person to examine, AI can do it and not get distracted, fatigued, or bored. This makes it a helpful tool for scientists to use.

Category
Sensing and processing methods, Architecture of sensing and perception systems, Meta-data contexts
Target audience
Individual Citizens/Members of the Society, Private Sector, Public Sector, Researchers and Academic
Source
Adra-e