Verzia zo dňa a času 08:26, 30. september 2010

The research of this group covers theoretical approaches and computational modelling of crucial phenomena in cognitive science, primarily related to language acquisition and processing. The learning methods focus on neural networks applied to various language subtasks (grammar learning, or lexical/sentence semantics), as well as a general adaptive method based on distinguishing criteria. Recent research goals include linking language learning with cognitive robotics.

Group members and their research focus

• Igor Farkaš - connectionist modeling of language learning, self-organization, neurorobotics
• Martin Takáč - cognitive semantics and knowledge representation, computational models of language emergence and language acquisition
• Ján Švantner (PhD student) - grammar learning with echo-state neural networks, sentence comprehension in visual world paradigm
• Michal Malý (PhD student) - intelligent agent design based on reinforcement learning
• Dana Retová (PhD student) - cognitive semantics
• Vladimir Chudy (PhD student) - human perception motivated speech recognition using neural networks
• Kristína Rebrová (PhD student) - (situated) language learning
• Ludovit Malinovsky(PhD student) - modeling the emergence of language as a collective cognitive activity

Past members

• Pavol Vančo (PhD student) - processing tree-structured data with recursive self-organizing neural networks - defended his thesis in September 2010. See his webpage.

Projects

• Modeling language as a complex system with self-organization (2008-2010, VEGA 1/0361/08)
• Modelling complex systems using neural networks with focus on linguistics (2005-2007, VEGA 1/2045/05)
• Cognitive science and traditional philosophical theories (2006-2008, VEGA 1/3612/06)
• Integrated model of autonomous meaning construction (2007, JPD 3 BA 2005/1-043)
• Environment for multi-agent systems specification (2006-2008, APVV-20-P04805)
• Cognitive semantics for dynamic environments (2006, UK/402/2006)