Магистратура
2026/2027
Воплощенный ИИ и нейровычислительная семантика
ID 1121860
Статус:
Курс по выбору (Науки о данных (Data Science))
Где читается:
Факультет компьютерных наук
Когда читается:
2-й курс, 2, 3 модуль
Охват аудитории:
для своего кампуса
Преподаватели:
Скрынникова Инна Валериевна
Язык:
английский
Кредиты:
6
Контактные часы:
40
Course Syllabus
Abstract
This graduate course explores the convergence of embodied cognition, artificial intelligence, computational linguistics and neurocomputational approaches to semantic representation. Grounded in the premise that meaning is rooted in sensorimotor experience, the course introduces Embodied Construction Grammar (ECG) as a formal model for representing language as structured simulations of perceptual and action-based schemas. Through a series of lectures and interactive seminars, students examine how intelligent agents—both biological and artificial—ground linguistic meaning in sensorimotor experience and environmental interaction. The curriculum critically evaluates contemporary paradigms such as language-conditioned reinforcement learning, multimodal foundation models with embodied interfaces that acquire semantics through physical interaction. Seminar sessions emphasize hands-on analysis of experimental methodologies, replication studies from embodied AI research. The course equips students to design and evaluate AI systems whose semantic capabilities emerge from situated interaction rather than purely statistical pattern recognition. Learning outcomes include the ability to critique disembodied language models, implement simple embodied semantic architectures, and articulate the theoretical foundations linking bodily experience to representational content in both natural and artificial intelligence.
Learning Objectives
- The course seeks to provide students with theoretical knowledge as well as hands-on skills in formalizing cognitive-linguistic theories into executable computational models, implementing simulation-based semantic engines that map sensorimotor schemas to abstract concepts, and integrating these neurocomputational architectures with contemporary embodied AI frameworks for language-conditioned robotic control and multimodal reasoning.
Expected Learning Outcomes
- formalizing cognitive-linguistic theories into executable computational models, including writing construction schemas that map sensorimotor schemas to linguistic constructions;
- implementing simulation-based semantic engines that ground abstract concepts in perceptual and action-based schemas, moving beyond symbolic or purely distributional representations;
- designing and evaluating neuro-symbolic architectures that integrate formal semantic representations with multimodal foundation models and language-conditioned robotic agents;
- critiquing and comparing disembodied vs. embodied language models, identifying the theoretical and empirical limitations of purely statistical approaches to semantic representation;
- conducting replication studies and experimental methodologies from embodied AI and cognitive linguistics research, including hands-on analysis of simulation-based language understanding systems;
- articulating the theoretical foundations linking neural computation, bodily experience, and representational content in both biological and artificial cognitive systems.
Course Contents
- Module 1: Foundations of Embodied Cognition and Neural Semantics Introduction to Embodied Cognition and the Neural Theory of Language (NTL)
- Image Schemas and Spatial Primitives as Semantic Building Blocks
- Neural Computation and the Biological Substrates of Meaning
- Conceptual Metaphor Theory and Cross-Domain Mappings
- Foundations of Embodied Construction Grammar (ECG): Syntax, Semantics, and Unification
- Simulation-Based Semantic Engines: Grounding Language in Perceptual-Motor Routines
- Module 2: Computational Modeling, Implementation, and Embodied AI Integration. Implementing ECG Grammars: Tools and Formalisms
- Neuro-Symbolic Architectures for Language and Action Integration
- Embodied AI in Practice: Language-Conditioned Robotics and Multimodal Agents
- Comparative Evaluation, Open Challenges, and Future Directions
Interim Assessment
- 2026/2027 3rd moduleFinal = 0.15 × HW_1_ECG + 0.15 × Test_M1_Theory + 0.10 × Sem_Active + 0.25 × HW_2_Simulation + 0.35 × Proj_Final
Bibliography
Recommended Core Bibliography
- Женщины, огонь и опасные вещи - Лакофф Дж. - Издательство "Языки славянских культур" - 5-94457-129-2 - 2003 - русский - https://e.lanbook.com/book/137043 - ЛАНЬ - 137043
Recommended Additional Bibliography
- Felin, T., & Holweg, M. (2024, December). Theory Is All You Need: AI, Human Cognition, and Causal Reasoning. Strategy Science, 9(4), 346-371
- Hoffmann, M. H. G. Transcendental arguments in Scientific Reasoning // Erkenntnis. 2019. Vol. 84, No. 6. P. 1387-1407.
- John Paul Minda. (2015). The Psychology of Thinking : Reasoning, Decision-Making and Problem-Solving. SAGE Publications Ltd.