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Abhijit Gosavi
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2020 – today
- 2024
- [j17]Abhijit Gosavi
, Vy K. Le:
Maintenance optimization in a digital twin for Industry 4.0. Ann. Oper. Res. 340(1): 245-269 (2024) - [j16]Abhijit Gosavi
Deep reinforcement learning for approximate policy iteration: convergence analysis and a post-earthquake disaster response case study. Optim. Lett. 18(9): 2033-2050 (2024) - 2022
- [j15]Carlos Chaves, Abhijit Gosavi
On general multi-server queues with non-poisson arrivals and medium traffic: a new approximation and a COVID-19 ventilator case study. Oper. Res. 22(5): 5205-5229 (2022) - 2020
- [j14]Abhijit Gosavi
Discrete-Event-Based Simulation Model for Performance Evaluation of Post-Earthquake Restoration in a Smart City. IEEE Trans. Engineering Management 67(3): 582-592 (2020) - [c13]Abhijit Gosavi:
The Actor-Critic Algorithm for Infinite Horizon Discounted Cost Revisited. WSC 2020: 2867-2878
2010 – 2019
- 2019
- [j13]Ryan J. Lawhead, Abhijit Gosavi:
A bounded actor-critic reinforcement learning algorithm applied to airline revenue management. Eng. Appl. Artif. Intell. 82: 252-262 (2019) - 2017
- [j12]Abhijit Gosavi
Predicting Response of Risk-Seeking Systems During Project Negotiations in a System of Systems. IEEE Syst. J. 11(3): 1557-1566 (2017) - 2016
- [j11]Abhijit Gosavi
Solving Markov decision processes with downside risk adjustment. Int. J. Autom. Comput. 13(3): 235-245 (2016) - 2015
- [c12]Abhijit Gosavi
Analyzing Responses from Likert Surveys and Risk-adjusted Ranking: A Data Analytics Perspective. Complex Adaptive Systems 2015: 24-31 - 2014
- [j10]Abhijit Gosavi
Variance-penalized Markov decision processes: dynamic programming and reinforcement learning techniques. Int. J. Gen. Syst. 43(6): 649-669 (2014) - [c11]Abhijit Gosavi
Beyond exponential utility functions: A variance-adjusted approach for risk-averse reinforcement learning. ADPRL 2014: 1-8 - [c10]Abhijit Gosavi
How to Rein in the Volatile Actor: A New Bounded Perspective. Complex Adaptive Systems 2014: 500-507 - 2013
- [c9]Abhijit Gosavi
Relative value iteration for average reward semi-Markov control via simulation. WSC 2013: 623-630 - 2012
- [c8]Abhijit Gosavi
Approximate Policy Iteration for Markov Control Revisited. Complex Adaptive Systems 2012: 90-95 - 2011
- [j9]Aykut F. Kahraman, Abhijit Gosavi
On the distribution of the number stranded in bulk-arrival, bulk-service queues of the M/G/1 form. Eur. J. Oper. Res. 212(2): 352-360 (2011) - [c7]Abhijit Gosavi
Model-building semi-Markov adaptive critics. ADPRL 2011: 170-175 - [c6]Abhijit Gosavi
Stochastic policy search for variance-penalized semi-Markov control. WSC 2011: 2865-2876 - [c5]Abhijit Gosavi
Approximate Policy Iteration for Semi-Markov Control Revisited. Complex Adaptive Systems 2011: 249-255 - 2010
- [c4]Abhijit Gosavi
Finite horizon Markov control with one-step variance penalties. Allerton 2010: 1355-1359
2000 – 2009
- 2009
- [j8]Abhijit Gosavi
Reinforcement Learning: A Tutorial Survey and Recent Advances. INFORMS J. Comput. 21(2): 178-192 (2009) - [c3]Abhijit Gosavi
Reinforcement Learning for Model Building and Variance-penalized Control. WSC 2009: 373-379 - 2008
- [j7]Aykut F. Kahraman, Abhijit Gosavi
Stochastic Modeling of an Automated Guided Vehicle System With One Vehicle and a Closed-Loop Path. IEEE Trans Autom. Sci. Eng. 5(3): 504-518 (2008) - [c2]Abhijit Gosavi
On step sizes, stochastic shortest paths, and survival probabilities in Reinforcement Learning. WSC 2008: 525-531 - 2007
- [j6]Ganesh Subramaniam, Abhijit Gosavi
Simulation-based optimisation for material dispatching in Vendor-Managed Inventory systems. Int. J. Simul. Process. Model. 3(4): 238-245 (2007) - [j5]Abhijit Gosavi
Simulation optimization for revenue management of airlines with cancellations and overbooking. OR Spectr. 29(1): 21-38 (2007) - 2006
- [j4]Abhijit Gosavi
A risk-sensitive approach to total productive maintenance. Autom. 42(8): 1321-1330 (2006) - [j3]Abhijit Gosavi
Boundedness of iterates in Q-Learning. Syst. Control. Lett. 55(4): 347-349 (2006) - 2004
- [j2]Abhijit Gosavi
Reinforcement learning for long-run average cost. Eur. J. Oper. Res. 155(3): 654-674 (2004) - [j1]Abhijit Gosavi
A Reinforcement Learning Algorithm Based on Policy Iteration for Average Reward: Empirical Results with Yield Management and Convergence Analysis. Mach. Learn. 55(1): 5-29 (2004) - [c1]Ganesh Subramaniam, Abhijit Gosavi:
Simulation-Based Optimization for Material Dispatching in a Retailer Network. WSC 2004: 1412-1417
Coauthor Index
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