User adaptation of human-robot interaction model based on Bayesian Network and introspection of interaction experience

IEEE International Conference on Intelligent Robots and Systems

Volumn 3, Issue , 2000, Pages 2139-2144

  Inamura, T ^a   Inaba, M ^a   Inoue, H ^a  

^a UNIVERSITY OF TOKYO   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

COLLISION AVOIDANCE; COMPUTER SIMULATION; GENETIC ALGORITHMS; HUMAN COMPUTER INTERACTION; MOBILE ROBOTS; NATURAL LANGUAGE PROCESSING SYSTEMS; NEURAL NETWORKS; SEMANTICS; SENSORS; STATE SPACE METHODS;

BAYESIAN NETWORK; HUMAN ROBOT INTERACTION; INTROSPECTION; USER ADAPTATION;

ROBOT LEARNING;

EID: 0034447963     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. Acquisition of probabilistic behavior decision model based on the interactive teaching method
2. Cooperative behavior acquisition for mobile robots in dynamically changing real worlds via vision-based reinforcement learning and development
3. Robot oriented state space construction
4. A decision-theoretic approach to planning perception and control
5. Acquiring a probabilistic map with dialogue-based learning
6. Real-World applications of bayesian networks
7. A bayesian approach for user modeling in dialogue systems
8. An expansion operator for interactive evolution