{"id":16784,"date":"2023-05-19T09:33:20","date_gmt":"2023-05-19T13:33:20","guid":{"rendered":"https:\/\/carleton.ca\/scs\/?post_type=cu_people&p=16784"},"modified":"2026-06-02T14:59:55","modified_gmt":"2026-06-02T18:59:55","slug":"zinovi-rabinovich","status":"publish","type":"cu_people","link":"https:\/\/carleton.ca\/scs\/people\/zinovi-rabinovich\/","title":{"rendered":"Zinovi Rabinovich"},"content":{"rendered":"
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\n \n \n \n <\/h1>\n\n \n <\/header>\n\n\n\n

Research Interests<\/h3>\n\n\n\n

Artificial Intelligence, Multi-Agent Systems, Multi-Agent Learning<\/p>\n\n\n\n

Specific Research Interests<\/h3>\n\n\n\n

Modelling of manipulative interactions, inclusive of machine-human interactions
\nPerceptual control and emergent behaviour<\/p>\n\n\n\n

Current Research<\/h3>\n\n\n\n

Current research projects focus largely on Behaviour Cultivation (a.k.a. Backdoor attacks, a.k.a. Environment Poisoning, a.k.a. Dynamic Difficulty Adjustment) against Reinforcement (Single, Multi-Agent, Distributed\/Federated) Learning. Naturally, we use deep learning methods, but also rely on game theory, information theory, and evolutionary\/genetic methods.<\/p>\n\n\n\n

With core methodology available, we now look into:<\/p>\n\n\n\n