Produktbild: Computational Collective Intelligence
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Computational Collective Intelligence 18th International Conference, ICCCI 2026, Heraklion, Crete, Greece, September 23–25, 2026, Proceedings, Part I

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

29.10.2026

Abbildungen

XII, 485 p. 121 illus.

Herausgeber

Ngoc Thanh Nguyen + weitere

Verlag

Springer

Seitenzahl

485

Maße (B/H)

15,5/23,5 cm

Sprache

Englisch

ISBN

978-3-032-36867-6

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

29.10.2026

Abbildungen

XII, 485 p. 121 illus.

Herausgeber

Verlag

Springer

Seitenzahl

485

Maße (B/H)

15,5/23,5 cm

Sprache

Englisch

ISBN

978-3-032-36867-6

Herstelleradresse

Springer Nature Customer Service Center GmbH
Europaplatz 3
69115 Heidelberg
DE
ProductSafety@springernature.com

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  • Produktbild: Computational Collective Intelligence
  • .- Collective Intelligence and Collective Decision-Making.

    .- The Hive Mind in Silicon: Situating Large Language Models within Computational Collective Intelligence.

    .- Measuring Fairness Metrics Robustness Through Collective Ranking Aggregation Under Controlled Bias Injections.

    .- CAF-Gen: A Multi-Agent System for Enriching Argumentation Structures.

    .- Sentiment drift and bias of agent collectives.

    .- Trajectory Separation for Scalable Credit Assignment in Cooperative Multi-Agent Reinforcement Learning.

    .- Evaluating the Robustness of Homogeneous Multi-Agent PPO Algorithm Against Observation Perturbations in Cooperative Multi-Agent Tasks.

    .- Formal Reasoning and Guidance Platform for Transparent Scaffolding for Multi-Agent Debate.

    .- A Conjunctive-Disjunctive Aggregation Framework for Asymmetric Interval Numbers.

    .- Epistemic Instrumental Convergence in Partially Observable Agents.

    .- Quantum for Collective.

    .- Dual-Quantum Vowel Recognition.

    .- Exploring Hamiltonian Control of a Quantum Walk Environment via Reinforcement Learning: A Case Study on the Traveling Salesman Problem.

    .- Volumetric Benchmarking of IQM-Spark: Parity-Preserving Quantum Volume and Compilation Overheads in Odra 5.

    .- Autoencoder-Based Hybrid Quantum Classification of MNIST on ODRA 5.

    .- Performance Analysis of the HHL Algorithm on the Odra 5 Quantum Computer.

    .- Collective Intelligence in Deep Learning Techniques.

    .- When Interpretable Parameters Fail to Explain: Evidence from the Rescorla–Wagner Model.

    .- Sparse Neural Code Representations for Reinforcement Learning with Linear Action-Value Function Approximation.

    .- A Systematic Explainability Framework for Hybrid Spatio-Temporal Models based on Integrated Gradients.

    .- Prompt-guided Resource-aware Neural Architecture Search for TinyML Object Detection Models.

    .- Benchmarking Deep Learning and Transformer-based Models for ECG Signal Imputation.

    .- Influence of Recursive Grouping of Neuron Inputs on Contextual Neural Networks in Classification Tasks.

    .- A Mahalanobis-Regularized Geometry-Aware Variational Autoencoder for Explainable Credit Card Fraud Detection.

    .- Edge QuantNet: An Ultralight Quantized SE-ResNet Architecture for Leaf Disease Classification on Resource-Constrained Devices.

    .- Natural Language Processing.

    .- Unveiling the Valence–Dominance Ratio: Toward Recognizing Emotions in Tunisian Speech.

    .- Study of Deepfake Audio Detection in Telephone Speech with Pretrained Self-Supervised Models.

    .- When Silence Matters: How VAD-driven Whisper Architectures reshape Temporal Alignment in Low-Resource Multilingual ASR.

    .- Personalized Alignment of Large Language Models.

    .- LLM Compression with Jointly Optimizing Architectural and Quantization choices.

    .- Collective Intelligence in Data Mining and Machine Learning.

    .- Macroscopic Design of Swarms with Collective State Machines.

    .- Reduction through Homogeneous Clustering with k-means++ Seeding.

    .- A Multimodal BiLSTM Model for Predicting Learner Question Performance Using Facial and Tabular Data.

    .- Interpretable Software Defect Prediction with Ensemble Models across Static and Process Metrics.

    .- Surrogate Modeling for Error Estimation in Time-Series Regression with CatBoost.

    .- A Novel Hybrid Ensemble Regression Framework for Residential Property Price Prediction in Athens Using Optimized Machine Learning Models.