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Computational Theory of Mind for Human-Machine Teams [electronic resource] : First International Symposium, ToM for Teams 2021, Virtual Event, November 4-6, 2021, Revised Selected Papers / edited by Nikolos Gurney, Gita Sukthankar.

Contributor(s): Gurney, Nikolos [editor.] | Sukthankar, Gita [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Computer Science: 13775Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2022Edition: 1st ed. 2022.Description: XII, 229 p. 62 illus., 50 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783031216718.Subject(s): Artificial intelligence | Application software | Computers | Machine theory | Artificial Intelligence | Computer and Information Systems Applications | Computing Milieux | Formal Languages and Automata TheoryAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Theory of Mind -- Operationalizing Theories of Theory of Mind: A Survey -- Knowledge of Self and Other Within a Broader Commonsense Setting -- Constructivist Approaches for Computational Emotions: A Systematic Survey -- Methodological Advances -- Social Cognition Paradigms ex Machinas -- Evaluating Artificial Social Intelligence in an Urban Search and Rescue Task Environment -- Modular Procedural Generation for Voxel Maps -- Task Complexity and Performance in Individuals and Groups Without Communication -- Development of Emergent Leadership Measurement: Implications for Human-Machine Teams -- Translating and Modeling Human Theory of Mind for ASI -- Should Agents Have Two Systems to Track Beliefs and Belief-Like States? -- Sequential Theory of Mind Modeling in Team Search and Rescue Tasks -- Integrating Machine Learning and Cognitive Modeling of Decision Making -- Overgenerality from Inference in Perspective-Taking -- Tools for Improving ASI -- Using Features at MultipleTemporal and Spatial Resolutions to Predict Human Behavior in Real Time -- Route Optimization in Service of a Search and Rescue Artificial Social Intelligence Agent.
In: Springer Nature eBookSummary: This book constitutes the proceedings of the First International Symposium, ToM for Teams 2021, held in Washington, DC, USA, during November 4-6, 2021, Each chapter in this section tackles a different aspect of AI representing the thoughts and beliefs of human agents. The work presented herein represents our collective efforts to better understand ToM, develop AI with ToM capabilities (ASI), and study how to integrate such systems into human teams.
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Theory of Mind -- Operationalizing Theories of Theory of Mind: A Survey -- Knowledge of Self and Other Within a Broader Commonsense Setting -- Constructivist Approaches for Computational Emotions: A Systematic Survey -- Methodological Advances -- Social Cognition Paradigms ex Machinas -- Evaluating Artificial Social Intelligence in an Urban Search and Rescue Task Environment -- Modular Procedural Generation for Voxel Maps -- Task Complexity and Performance in Individuals and Groups Without Communication -- Development of Emergent Leadership Measurement: Implications for Human-Machine Teams -- Translating and Modeling Human Theory of Mind for ASI -- Should Agents Have Two Systems to Track Beliefs and Belief-Like States? -- Sequential Theory of Mind Modeling in Team Search and Rescue Tasks -- Integrating Machine Learning and Cognitive Modeling of Decision Making -- Overgenerality from Inference in Perspective-Taking -- Tools for Improving ASI -- Using Features at MultipleTemporal and Spatial Resolutions to Predict Human Behavior in Real Time -- Route Optimization in Service of a Search and Rescue Artificial Social Intelligence Agent.

This book constitutes the proceedings of the First International Symposium, ToM for Teams 2021, held in Washington, DC, USA, during November 4-6, 2021, Each chapter in this section tackles a different aspect of AI representing the thoughts and beliefs of human agents. The work presented herein represents our collective efforts to better understand ToM, develop AI with ToM capabilities (ASI), and study how to integrate such systems into human teams.

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