reinforcement learning | Robert Bosch Center for Data Science and Artificial Intelligence

events

RBCDSAI LatentView Colloquium Series

December 19 03:30 PM to 05:30 PM

ICSR Auditorium , IIT Madras

colloquium , reinforcement learning

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people

Balaraman Ravindran

Head, Robert Bosch Centre for Data Science and AI

Professor

Mindtree Faculty Fellow

Machine learning, Reinforcement learning, Social Network Analysis, Data and text mining

Chandra Shekar Lakshminarayanan

Assistant Professor at Department of Computer Science And Engineering, IIT Palakkad

reinforcement learning, stochastic control and deep learning

Depen Morwani

MS Scholar

Reinforcement Learning, Theoretical Deep Learning

Ashutosh Dilipbhai Kakadiya

MS Scholar

Reinforcement Learning, Relational Learning, Applied ML

Dhruv Ramani

Project Associate

Reinforcement Learning, Deep Learning

Debargha Bhattacharjee

MS Scholar

Natural Language Processing, Reinforcement Learning

Aravind Venugopal

Post Baccalaureate Fellow

Reinforcement Learning, Game theory

Pavan Ravishankar

MS Scholar

Causal Inference, Reinforcement Learning

Jahnvi Patel

Dual Degree

Reinforcement Learning

Harshavardhan P V

Dual Degree

Reinforcement learning, Network reprsentation learning

Chandrasekar Subramanian

PhD Scholar

Reinforcement learning

Anand A R

Dual degree

Reinforcement Learning, Applied deep learning, Comutational biology

Manikandan

PhD Scholar

Model Predictive controllers, Process control, Reinforcement learning

Sivapriya Vellaichamy

Post Baccalaureate Fellow

Deep Learning, Reinforcement Learning

Raghavendra Mallela

Project Associate

Reinforcement Learning, Stochastic Modeling

Manoj Bharadhwaj

MS Scholar

Deep Learning, Reinforcement Learning, Intelligent Transportation Systems, Explainable AI

Siddharth Nishtala

MS Scholar

Deep Learning, Reinforcement Learning

Anagha Zachariah

Project Associate

Reinforcement learning, Data science", Machine Learning"

projects

Mitesh M Khapra

Attention Mechanisms in Deep Neural Networks

deep learning reinforcement learning transfer learning attention mechanism in deep learning natural language processing

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Nandan Sudarsanam

Learning With Limited Partial and Noisy Data

reinforcement learning applied statistics

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publications

RePReL: Integrating Relational Planning and Reinforcement Learning for Effective Abstraction

Harsha Kokel , Arjun Manoharan , Sriraam Natarajan and more

To appear in the Proceedings of the 31st International Conference on Automated Planning and Scheduling

Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty

Aravind Venugopal , Elizabeth Bondi , Harshavardhan Kamarthi and more

To appear in the Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021)

Sample Efficient Ensemble Reinforcement Learning

Rohan Saphal , B Ravindran , Dheevatsa Mudigere and more

To appear in the Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2021)

An Enhanced Advising Model in Teacher-Student framework using State Categorization

Daksh Anand , Vaibhav Gupta , Praveen Paruchuri and more

To appear in the Proceedings of the Thirty-Fifth Annual Conference of the Association for Advancement of Artificial Intelligence (AAAI 2021)

Reinforcement Learning for Multi-Product Multi-Node Inventory Management in Supply Chains

Nazneen N Sultana , Hardik Meisheri , Vinita Baniwal and more

arXiv:2006.04037

Dynamic Action Repetition for Deep Reinforcement Learning

Aravind S Lakshminarayanan , Sahil Sharma , B Ravindran

Proceedings of the AAAI Conference on Artificial Intelligence

EPOpt: Learning Robust Neural Network Policies Using Model Ensembles

Aravind Rajeswaran , Sarvjeet Ghotra , Sergey Levine and more

ICLR

Dynamic frame skip deep q network

Aravind S Lakshminarayanan , Sahil Sharma , B Ravindran

IJCAI 2016 Workshop on Deep Reinforcement Learning: Frontiers and Challenges

An extended reinforcement learning model of basal ganglia to understand the contributions of serotonin and dopamine in risk-based decision making, reward prediction, and punishment learning

Pragathi P Balasubramani , V Srinivasa Chakravarthy , B Ravindran and more

Frontiers in computational neuroscience

research

Safety and Stability Preserving Reinforcement Learning

reinforcement learning deep learning control theory autonomous systems

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Attention Mechanisms in Deep Neural Networks

neural networks reinforcement learning attention mechanism

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