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pro vyhledávání: '"Mohalik, Swarup Kumar"'
Spiking Neural Networks (SNNs) are a subclass of neuromorphic models that have great potential to be used as controllers in Cyber-Physical Systems (CPSs) due to their energy efficiency. They can benefit from the prevalent approach of first training a
Externí odkaz:
http://arxiv.org/abs/2408.01996
Autor:
Karapantelakis, Athanasios, Nikou, Alexandros, Kattepur, Ajay, Martins, Jean, Mokrushin, Leonid, Mohalik, Swarup Kumar, Orlic, Marin, Feljan, Aneta Vulgarakis
In the near future, mobile networks are expected to broaden their services and coverage to accommodate a larger user base and diverse user needs. Thus, they will increasingly rely on artificial intelligence (AI) to manage network operation and contro
Externí odkaz:
http://arxiv.org/abs/2404.06946
Neural networks are now extensively used in perception, prediction and control of autonomous systems. Their deployment in safety-critical systems brings forth the need for verification techniques for such networks. As an alternative to exhaustive and
Externí odkaz:
http://arxiv.org/abs/2104.12418
Autor:
Gupta, Nikunj, Srinivasaraghavan, G, Mohalik, Swarup Kumar, Kumar, Nishant, Taylor, Matthew E.
Cooperative multi-agent reinforcement learning (MARL) has achieved significant results, most notably by leveraging the representation-learning abilities of deep neural networks. However, large centralized approaches quickly become infeasible as the n
Externí odkaz:
http://arxiv.org/abs/2102.00824
Autor:
Cyras, Kristijonas, Badrinath, Ramamurthy, Mohalik, Swarup Kumar, Mujumdar, Anusha, Nikou, Alexandros, Previti, Alessandro, Sundararajan, Vaishnavi, Feljan, Aneta Vulgarakis
As a field of AI, Machine Reasoning (MR) uses largely symbolic means to formalize and emulate abstract reasoning. Studies in early MR have notably started inquiries into Explainable AI (XAI) -- arguably one of the biggest concerns today for the AI co
Externí odkaz:
http://arxiv.org/abs/2009.00418
Intelligent Cyber-physical systems can be modelled as multi-agent systems with planning capability to impart adaptivity for changing contexts. In such multi-agent systems, the protocol for plan execution must result in the proper completion and order
Externí odkaz:
http://arxiv.org/abs/1812.07219
Antifragile systems grow measurably better in the presence of hazards. This is in contrast to fragile systems which break down in the presence of hazards, robust systems that tolerate hazards up to a certain degree, and resilient systems that -- like
Externí odkaz:
http://arxiv.org/abs/1802.09159
Akademický článek
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Publikováno v:
ACM SIGSOFT Software Engineering Notes; January 2018, Vol. 42 Issue: 4 p25-27, 3p
Publikováno v:
ACM International Conference Proceeding Series; 2/5/2017, p221-222, 2p