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Similar Items: Artificial Motivation for Cognitive Software Agents

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Talk to Your Data: An Agentic Artificial Intelligence‐Driven Decision‐Support Framework for Prosumer Energy Optimization and Recommendations
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Fully moral artificial agents: future or fiction
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Homeostatic Agent for General Environment
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Heterogeneity in Agent-Based Models
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On Defining Artificial Intelligence
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Special Issue on the Exploration of Cognitive Architectures Editorial
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From Idea to Implementation: Evaluating the Influence of Large Language Models in Software Development—An Opinion Paper
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Multimodal Neurons in Artificial Neural Networks
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Learning and decision-making in artificial animals
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Agent-based adaptive e-learning model for any learning management system
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Combating Money Laundering using Artificial Intelligence
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Intelligence via ultrafilters: structural properties of some intelligence comparators of deterministic Legg-Hutter agents
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Generating a Contact Matrix for Aged Care Settings in Australia: An Agent-Based Model Study
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A New Approach to Creation of an Artificial Intellect and Method of its Implementation
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H2CD: Semantic‐Enhanced Heterogeneous Hypergraph Network With Large Language Model for Cognitive Diagnosis
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Artificial Intelligence in Music: A Bibliometric and Systematic Review of Creation, Performance, and Education
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Study on One Kind of Three- dimensional Virtual Model of Teaching Based on Artificial Intelligence
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Correction to “Development of a Chemically Driven Biomimetic Modular Artificial Muscle (BiMAM)”
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Safe integration of Large Language Models into industrial process control: a multi-agent architecture with P&ID-grounded validation
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UAV swarm communication networking and routing optimization for high-demand users: a graph attention multi-agent reinforcement learning approach
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Unveiling Multiple Sclerosis Predictors: A Proposed Artificial Intelligence Approach Using Associative Classification
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Cognitive Mapping in Ottoman-Turkish Music: A Machine Learning Approach to Modal Transitions (16th–19th Centuries)
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Artificial Neural Network Surrogate Modelling for Predicting and Optimising CO2 Conversion to Methanol Under Uncertainty