activity
20202025
most citedLearning Skills to Navigate without a Master: A Sequential Multi-Policy Reinforcement Learning Algorithm

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

q-fin.ST2025

Predictive AI with External Knowledge Infusion: Datasets and Benchmarks for Stock Markets

Ambedkar Dukkipati, Kawin Mayilvaghanan, Naveen Kumar Pallekonda +2

Fluctuations in stock prices are influenced by a complex interplay of factors that go beyond mere historical data. These factors, themselves influenced by external forces, encompas…

cs.LG2024

Active Reinforcement Learning Strategies for Offline Policy Improvement

Ambedkar Dukkipati, Ranga Shaarad Ayyagari, Bodhisattwa Dasgupta +2

Learning agents that excel at sequential decision-making tasks must continuously resolve the problem of exploration and exploitation for optimal learning. However, such interaction…

cs.LG2024

Temporal Abstraction in Reinforcement Learning with Offline Data

Ranga Shaarad Ayyagari, Anurita Ghosh, Ambedkar Dukkipati

Standard reinforcement learning algorithms with a single policy perform poorly on tasks in complex environments involving sparse rewards, diverse behaviors, or long-term planning.…

cs.LG2023

Reinforcement Learning under External Influence: Guarantees, Algorithms, and Sample Complexity

Ranga Shaarad Ayyagari, Revanth Raj Eega, Ambedkar Dukkipati

In this paper, we study the problem of reinforcement learning under the influence of external events. For this, we consider Markov decision processes with continuous state and acti…

cs.LG2021

Risk-Aware Algorithms for Combinatorial Semi-Bandits

Shaarad Ayyagari, Ambedkar Dukkipati

In this paper, we study the stochastic combinatorial multi-armed bandit problem under semi-bandit feedback. While much work has been done on algorithms that optimize the expected r…

cs.AI2021★ 1 cited

Learning Skills to Navigate without a Master: A Sequential Multi-Policy Reinforcement Learning Algorithm

Ambedkar Dukkipati, Rajarshi Banerjee, Ranga Shaarad Ayyagari +1

Solving complex problems using reinforcement learning necessitates breaking down the problem into manageable tasks and learning policies to solve these tasks. These policies, in tu…