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AI 2023: Advances in Artificial Intelligence

Overview of attention for book
Cover of 'AI 2023: Advances in Artificial Intelligence'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Collaborative Qualitative Environment Mapping
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    Chapter 2 Towards Learning Action Models from Narrative Text Through Extraction and Ordering of Structured Events
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    Chapter 3 The Difficulty of Novelty Detection and Adaptation in Physical Environments
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    Chapter 4 Lateral AI: Simulating Diversity in Virtual Communities
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    Chapter 5 Reports, Observations, and Belief Change
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    Chapter 6 A Prompting Framework to Enhance Language Model Output
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    Chapter 7 Epistemic Reasoning in Computational Machine Ethics
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    Chapter 8 Using Social Sensing to Validate Flood Risk Modelling in England
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    Chapter 9 Symbolic Data Analysis to Improve Completeness of Model Combination Methods
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    Chapter 10 CySpider: A Neural Semantic Parsing Corpus with Baseline Models for Property Graphs
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    Chapter 11 S5TR: Simple Single Stage Sequencer for Scene Text Recognition
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    Chapter 12 Coping with Data Distribution Shifts: XAI-Based Adaptive Learning with SHAP Clustering for Energy Consumption Prediction
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    Chapter 13 Concept-Guided Interpretable Federated Learning
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    Chapter 14 Systematic Analysis of the Impact of Label Noise Correction on ML Fairness
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    Chapter 15 Part-Aware Prototype-Aligned Interpretable Image Classification with Basic Feature Domain
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    Chapter 16 Hybrid CNN-Interpreter: Interprete Local and Global Contexts for CNN-Based Models
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    Chapter 17 Impact of Fidelity and Robustness of Machine Learning Explanations on User Trust
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    Chapter 18 Interpretable Drawing Psychoanalysis via House-Tree-Person Test
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    Chapter 19 A Non-asymptotic Risk Bound for Model Selection in a High-Dimensional Mixture of Experts via Joint Rank and Variable Selection
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    Chapter 20 Auction-Based Allocation of Location-Specific Tasks
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    Chapter 21 Generalized Bargaining Protocols
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    Chapter 22 SAGE: Generating Symbolic Goals for Myopic Models in Deep Reinforcement Learning
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    Chapter 23 Leaving the NavMesh: An Ablative Analysis of Deep Reinforcement Learning for Complex Navigation in 3D Virtual Environments
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    Chapter 24 Transformed Successor Features for Transfer Reinforcement Learning
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    Chapter 25 Cooperative Multi-Agent Reinforcement Learning with Dynamic Target Localization: A Reward Sharing Approach
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    Chapter 26 Competitive Collaboration for Complex Task Learning in Agent Systems
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    Chapter 27 Limiting Inequalities in Repeated House and Task Allocation
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    Chapter 28 Non-stationarity Detection in Model-Free Reinforcement Learning via Value Function Monitoring
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    Chapter 29 Toward a Unified Framework for RGB and RGB-D Visual Navigation
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    Chapter 30 Improving CCA Algorithms on SSVEP Classification with Reinforcement Learning Based Temporal Filtering
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    Chapter 31 Evolving Epidemic Management Rules Using Deep Neuroevolution: A Novel Approach to Inspection Scheduling and Outbreak Minimization
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    Chapter 32 A Semantic Genetic Programming Approach to Evolving Heuristics for Multi-objective Dynamic Scheduling
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    Chapter 33 XC-NAS: A New Cellular Encoding Approach for Neural Architecture Search of Multi-path Convolutional Neural Networks
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    Chapter 34 Bloating Reduction in Symbolic Regression Through Function Frequency-Based Tree Substitution in Genetic Programming
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    Chapter 35 Generating Collective Motion Behaviour Libraries Using Developmental Evolution
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    Chapter 36 A Group Genetic Algorithm for Energy-Efficient Resource Allocation in Container-Based Clouds with Heterogeneous Physical Machines
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    Chapter 37 Genetic Programming with Adaptive Reference Points for Pareto Local Search in Many-Objective Job Shop Scheduling
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    Chapter 38 A Study of Fitness Gains in Evolving Finite State Machines
Attention for Chapter 33: XC-NAS: A New Cellular Encoding Approach for Neural Architecture Search of Multi-path Convolutional Neural Networks
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Chapter title
XC-NAS: A New Cellular Encoding Approach for Neural Architecture Search of Multi-path Convolutional Neural Networks
Chapter number 33
Book title
AI 2023: Advances in Artificial Intelligence
Published in
arXiv, January 2024
DOI 10.1007/978-981-99-8391-9_33
Book ISBNs
978-9-81-998390-2, 978-9-81-998391-9
Authors

Londt, Trevor, Gao, Xiaoying, Andreae, Peter, Mei, Yi, Trevor Londt, Xiaoying Gao, Peter Andreae, Yi Mei

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
 Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 100%
Readers by discipline Count As %
Physics and Astronomy 1 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 December 2023.
All research outputs
#22,397,502
of 24,988,588 outputs
Outputs from arXiv
#740,722
of 1,019,278 outputs
Outputs of similar age
#82,101
of 103,490 outputs
Outputs of similar age from arXiv
#4,280
of 9,991 outputs
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So far Altmetric has tracked 1,019,278 research outputs from this source. They receive a mean Attention Score of 4.1. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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